the ibm almaden resarch center , san jose, ca
TRANSCRIPT
Source ndash J Kreulen
The IBM Almaden Resarch Center San Jose Ca
Source Jeff Kreulen
Simple Project - Current Activities
IBM Almaden Resarch Center
Stephen K Boyer PhD sboyerusibmcom 408- 858-5544
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text [Text + Annotation]
- - - - - - - - - - - - - - - - - - - -
Annotated Text
Identify every chemical name
Convert all chem names into their chemical structures [SMILES] - then convert these SMILES Into inchirsquos amp Inchkeys (a unique identifier for the chemical)
- - - - - - - - - - - - - - - - - - - -
Annotate augment all chemical names with the term ldquoinchikey amp the unique inchikeyrdquo for that chemical The InChiKeys are now indexed as-if they were words (text) in the document
Re-index the augmented text [inchikeys] w SOLR
= aspirin = inchikey = BSYNRYMUTXBXSQ-UHFFFAOYSA-N
= aspirin = SMILE string = CC(=O)OC1=CC=CC=C1C(=O)O
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification of chemical names
Text Index + Annotation Index
Add the derived structures + annotations (amp meta data) to our master database
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text [Text + Annotation]
- - - - - - - - - - - - - - - - - - - -
Annotated Text
Identify every chemical name
Convert all chem names into their chemical structures [SMILES] - then convert these SMILES Into inchirsquos amp Inchkeys (a unique identifier for the chemical)
- - - - - - - - - - - - - - - - - - - -
Annotate augment all chemical names with the term ldquoinchikey amp the unique inchikeyrdquo for that chemical The InChiKeys are now indexed as-if they were words (text) in the document
Re-index the augmented text [inchikeys] w SOLR
= aspirin = inchikey = BSYNRYMUTXBXSQ-UHFFFAOYSA-N
= aspirin = SMILE string = CC(=O)OC1=CC=CC=C1C(=O)O
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification of chemical names
Text Index + Annotation Index
Add the derived structures + annotations (amp meta data) to our master database
ChemAxon [Name= Structure]
Chem Libraries J Chem Base
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text [ Text + Annotations]
identify all targets [Gene names amp their synonyms ]
Augment all target names with a ldquotag = geneid ldquo amp the NCBI unique Identifier for that target
- - - - - - - - - - - - - - - - - - - -
Re-index the augmentented text + geneid identifiers w SOLR
= JAK3 + Aliases = geneid = geneid=NCBIID = 3718
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification for targets (=geneidrsquos)
Annotated Text Index
Add the derived annotations (amp meta data) to our master database
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text Text + Annotation
Identify all known MeSH terms [for example diseases (C01) or signs amp symptoms (C23)
Identified amp augment every occurrence of every MeSh term with a lsquotag = MeSH amp the specific MeSh code Identifier
- - - - - - - - - - - - - - - - - - - -
Re-index the augmented text + the MeSh tags w SOLR
= Headache + = MeSH term + = C23 sign or symptom
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification for MeSh terms
Text Index + Annotation Index
Text = Headache
New index of original text plus all of itrsquos associated annotated information
Add the derived annotations (amp meta data) to our master database
A Sample Augmented text
ldquoInteractions of ibogaine and D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] in vivo microdialysis and motor behavior in rats Ibogaine an indolalkylamine has been proposed for use in treating stimulant addiction In the present study we sought to determine if ibogaine had any effects on the neurochemical and motor changes induced by D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] that would substantiate the anti-addictive claim Ibogaine (40 mgkg ip) injected 19 h prior to a D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] challenge (125 mgkg ip) potentiated the expected rise in extracellular dopamine[ibmentity type=drug name=dopamine value=dopamine chebitype=pharmacological roleneurotransmitter agent] levels in the striatum[ibmentity type=target name=striatum value=striatum targettype=tissue] and in the nucleus accumbens as measured by microdialysis in freely moving rats Using helliprdquo
Examples - why this is important and what it enables us to do that we could not easily do before -
Batch Analysis
For Example You are about to file a patent application ndash that contains
~ 300 ndash 400 chemical compounds How do you know if any
of these (400+) compounds has been patented before
Paste a list of InChIkeys to be batch searched here
Input list of InChIkeys to be batch searched here
1
2
Click run search
Results form batch search of InChikeys
Diavan Glipazol Ibuprofen Asprin Lotensin ImItrex Nabumetone Tessalon Sulfamethoxazole Trimethoprim Cyclobenzaprine Guaifenesin Oxymetazoline Anvitoff Dextromethorphan Lyrica Celexa
One can readily search hundreds or even thousands of compounds at at time ndash to see if any of the compounds have already been patented - amp by whom amp for what purpose
Exploring co-table analysis of Molecules with Gene IDrsquos
For example ndash show me all of the co-occurrences of these (x) molecules with these (any all) genersquos
From the main menu select the Analyze tab 1
2 From the analyze menu select the Cotable tab
3 Now Enter the Inchi keys for the molecules of interest -
Click here to enter a sample (test) set of molecules
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
Simple Project - Current Activities
IBM Almaden Resarch Center
Stephen K Boyer PhD sboyerusibmcom 408- 858-5544
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text [Text + Annotation]
- - - - - - - - - - - - - - - - - - - -
Annotated Text
Identify every chemical name
Convert all chem names into their chemical structures [SMILES] - then convert these SMILES Into inchirsquos amp Inchkeys (a unique identifier for the chemical)
- - - - - - - - - - - - - - - - - - - -
Annotate augment all chemical names with the term ldquoinchikey amp the unique inchikeyrdquo for that chemical The InChiKeys are now indexed as-if they were words (text) in the document
Re-index the augmented text [inchikeys] w SOLR
= aspirin = inchikey = BSYNRYMUTXBXSQ-UHFFFAOYSA-N
= aspirin = SMILE string = CC(=O)OC1=CC=CC=C1C(=O)O
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification of chemical names
Text Index + Annotation Index
Add the derived structures + annotations (amp meta data) to our master database
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text [Text + Annotation]
- - - - - - - - - - - - - - - - - - - -
Annotated Text
Identify every chemical name
Convert all chem names into their chemical structures [SMILES] - then convert these SMILES Into inchirsquos amp Inchkeys (a unique identifier for the chemical)
- - - - - - - - - - - - - - - - - - - -
Annotate augment all chemical names with the term ldquoinchikey amp the unique inchikeyrdquo for that chemical The InChiKeys are now indexed as-if they were words (text) in the document
Re-index the augmented text [inchikeys] w SOLR
= aspirin = inchikey = BSYNRYMUTXBXSQ-UHFFFAOYSA-N
= aspirin = SMILE string = CC(=O)OC1=CC=CC=C1C(=O)O
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification of chemical names
Text Index + Annotation Index
Add the derived structures + annotations (amp meta data) to our master database
ChemAxon [Name= Structure]
Chem Libraries J Chem Base
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text [ Text + Annotations]
identify all targets [Gene names amp their synonyms ]
Augment all target names with a ldquotag = geneid ldquo amp the NCBI unique Identifier for that target
- - - - - - - - - - - - - - - - - - - -
Re-index the augmentented text + geneid identifiers w SOLR
= JAK3 + Aliases = geneid = geneid=NCBIID = 3718
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification for targets (=geneidrsquos)
Annotated Text Index
Add the derived annotations (amp meta data) to our master database
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text Text + Annotation
Identify all known MeSH terms [for example diseases (C01) or signs amp symptoms (C23)
Identified amp augment every occurrence of every MeSh term with a lsquotag = MeSH amp the specific MeSh code Identifier
- - - - - - - - - - - - - - - - - - - -
Re-index the augmented text + the MeSh tags w SOLR
= Headache + = MeSH term + = C23 sign or symptom
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification for MeSh terms
Text Index + Annotation Index
Text = Headache
New index of original text plus all of itrsquos associated annotated information
Add the derived annotations (amp meta data) to our master database
A Sample Augmented text
ldquoInteractions of ibogaine and D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] in vivo microdialysis and motor behavior in rats Ibogaine an indolalkylamine has been proposed for use in treating stimulant addiction In the present study we sought to determine if ibogaine had any effects on the neurochemical and motor changes induced by D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] that would substantiate the anti-addictive claim Ibogaine (40 mgkg ip) injected 19 h prior to a D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] challenge (125 mgkg ip) potentiated the expected rise in extracellular dopamine[ibmentity type=drug name=dopamine value=dopamine chebitype=pharmacological roleneurotransmitter agent] levels in the striatum[ibmentity type=target name=striatum value=striatum targettype=tissue] and in the nucleus accumbens as measured by microdialysis in freely moving rats Using helliprdquo
Examples - why this is important and what it enables us to do that we could not easily do before -
Batch Analysis
For Example You are about to file a patent application ndash that contains
~ 300 ndash 400 chemical compounds How do you know if any
of these (400+) compounds has been patented before
Paste a list of InChIkeys to be batch searched here
Input list of InChIkeys to be batch searched here
1
2
Click run search
Results form batch search of InChikeys
Diavan Glipazol Ibuprofen Asprin Lotensin ImItrex Nabumetone Tessalon Sulfamethoxazole Trimethoprim Cyclobenzaprine Guaifenesin Oxymetazoline Anvitoff Dextromethorphan Lyrica Celexa
One can readily search hundreds or even thousands of compounds at at time ndash to see if any of the compounds have already been patented - amp by whom amp for what purpose
Exploring co-table analysis of Molecules with Gene IDrsquos
For example ndash show me all of the co-occurrences of these (x) molecules with these (any all) genersquos
From the main menu select the Analyze tab 1
2 From the analyze menu select the Cotable tab
3 Now Enter the Inchi keys for the molecules of interest -
Click here to enter a sample (test) set of molecules
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text [Text + Annotation]
- - - - - - - - - - - - - - - - - - - -
Annotated Text
Identify every chemical name
Convert all chem names into their chemical structures [SMILES] - then convert these SMILES Into inchirsquos amp Inchkeys (a unique identifier for the chemical)
- - - - - - - - - - - - - - - - - - - -
Annotate augment all chemical names with the term ldquoinchikey amp the unique inchikeyrdquo for that chemical The InChiKeys are now indexed as-if they were words (text) in the document
Re-index the augmented text [inchikeys] w SOLR
= aspirin = inchikey = BSYNRYMUTXBXSQ-UHFFFAOYSA-N
= aspirin = SMILE string = CC(=O)OC1=CC=CC=C1C(=O)O
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification of chemical names
Text Index + Annotation Index
Add the derived structures + annotations (amp meta data) to our master database
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text [Text + Annotation]
- - - - - - - - - - - - - - - - - - - -
Annotated Text
Identify every chemical name
Convert all chem names into their chemical structures [SMILES] - then convert these SMILES Into inchirsquos amp Inchkeys (a unique identifier for the chemical)
- - - - - - - - - - - - - - - - - - - -
Annotate augment all chemical names with the term ldquoinchikey amp the unique inchikeyrdquo for that chemical The InChiKeys are now indexed as-if they were words (text) in the document
Re-index the augmented text [inchikeys] w SOLR
= aspirin = inchikey = BSYNRYMUTXBXSQ-UHFFFAOYSA-N
= aspirin = SMILE string = CC(=O)OC1=CC=CC=C1C(=O)O
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification of chemical names
Text Index + Annotation Index
Add the derived structures + annotations (amp meta data) to our master database
ChemAxon [Name= Structure]
Chem Libraries J Chem Base
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text [ Text + Annotations]
identify all targets [Gene names amp their synonyms ]
Augment all target names with a ldquotag = geneid ldquo amp the NCBI unique Identifier for that target
- - - - - - - - - - - - - - - - - - - -
Re-index the augmentented text + geneid identifiers w SOLR
= JAK3 + Aliases = geneid = geneid=NCBIID = 3718
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification for targets (=geneidrsquos)
Annotated Text Index
Add the derived annotations (amp meta data) to our master database
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text Text + Annotation
Identify all known MeSH terms [for example diseases (C01) or signs amp symptoms (C23)
Identified amp augment every occurrence of every MeSh term with a lsquotag = MeSH amp the specific MeSh code Identifier
- - - - - - - - - - - - - - - - - - - -
Re-index the augmented text + the MeSh tags w SOLR
= Headache + = MeSH term + = C23 sign or symptom
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification for MeSh terms
Text Index + Annotation Index
Text = Headache
New index of original text plus all of itrsquos associated annotated information
Add the derived annotations (amp meta data) to our master database
A Sample Augmented text
ldquoInteractions of ibogaine and D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] in vivo microdialysis and motor behavior in rats Ibogaine an indolalkylamine has been proposed for use in treating stimulant addiction In the present study we sought to determine if ibogaine had any effects on the neurochemical and motor changes induced by D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] that would substantiate the anti-addictive claim Ibogaine (40 mgkg ip) injected 19 h prior to a D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] challenge (125 mgkg ip) potentiated the expected rise in extracellular dopamine[ibmentity type=drug name=dopamine value=dopamine chebitype=pharmacological roleneurotransmitter agent] levels in the striatum[ibmentity type=target name=striatum value=striatum targettype=tissue] and in the nucleus accumbens as measured by microdialysis in freely moving rats Using helliprdquo
Examples - why this is important and what it enables us to do that we could not easily do before -
Batch Analysis
For Example You are about to file a patent application ndash that contains
~ 300 ndash 400 chemical compounds How do you know if any
of these (400+) compounds has been patented before
Paste a list of InChIkeys to be batch searched here
Input list of InChIkeys to be batch searched here
1
2
Click run search
Results form batch search of InChikeys
Diavan Glipazol Ibuprofen Asprin Lotensin ImItrex Nabumetone Tessalon Sulfamethoxazole Trimethoprim Cyclobenzaprine Guaifenesin Oxymetazoline Anvitoff Dextromethorphan Lyrica Celexa
One can readily search hundreds or even thousands of compounds at at time ndash to see if any of the compounds have already been patented - amp by whom amp for what purpose
Exploring co-table analysis of Molecules with Gene IDrsquos
For example ndash show me all of the co-occurrences of these (x) molecules with these (any all) genersquos
From the main menu select the Analyze tab 1
2 From the analyze menu select the Cotable tab
3 Now Enter the Inchi keys for the molecules of interest -
Click here to enter a sample (test) set of molecules
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text [Text + Annotation]
- - - - - - - - - - - - - - - - - - - -
Annotated Text
Identify every chemical name
Convert all chem names into their chemical structures [SMILES] - then convert these SMILES Into inchirsquos amp Inchkeys (a unique identifier for the chemical)
- - - - - - - - - - - - - - - - - - - -
Annotate augment all chemical names with the term ldquoinchikey amp the unique inchikeyrdquo for that chemical The InChiKeys are now indexed as-if they were words (text) in the document
Re-index the augmented text [inchikeys] w SOLR
= aspirin = inchikey = BSYNRYMUTXBXSQ-UHFFFAOYSA-N
= aspirin = SMILE string = CC(=O)OC1=CC=CC=C1C(=O)O
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification of chemical names
Text Index + Annotation Index
Add the derived structures + annotations (amp meta data) to our master database
ChemAxon [Name= Structure]
Chem Libraries J Chem Base
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text [ Text + Annotations]
identify all targets [Gene names amp their synonyms ]
Augment all target names with a ldquotag = geneid ldquo amp the NCBI unique Identifier for that target
- - - - - - - - - - - - - - - - - - - -
Re-index the augmentented text + geneid identifiers w SOLR
= JAK3 + Aliases = geneid = geneid=NCBIID = 3718
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification for targets (=geneidrsquos)
Annotated Text Index
Add the derived annotations (amp meta data) to our master database
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text Text + Annotation
Identify all known MeSH terms [for example diseases (C01) or signs amp symptoms (C23)
Identified amp augment every occurrence of every MeSh term with a lsquotag = MeSH amp the specific MeSh code Identifier
- - - - - - - - - - - - - - - - - - - -
Re-index the augmented text + the MeSh tags w SOLR
= Headache + = MeSH term + = C23 sign or symptom
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification for MeSh terms
Text Index + Annotation Index
Text = Headache
New index of original text plus all of itrsquos associated annotated information
Add the derived annotations (amp meta data) to our master database
A Sample Augmented text
ldquoInteractions of ibogaine and D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] in vivo microdialysis and motor behavior in rats Ibogaine an indolalkylamine has been proposed for use in treating stimulant addiction In the present study we sought to determine if ibogaine had any effects on the neurochemical and motor changes induced by D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] that would substantiate the anti-addictive claim Ibogaine (40 mgkg ip) injected 19 h prior to a D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] challenge (125 mgkg ip) potentiated the expected rise in extracellular dopamine[ibmentity type=drug name=dopamine value=dopamine chebitype=pharmacological roleneurotransmitter agent] levels in the striatum[ibmentity type=target name=striatum value=striatum targettype=tissue] and in the nucleus accumbens as measured by microdialysis in freely moving rats Using helliprdquo
Examples - why this is important and what it enables us to do that we could not easily do before -
Batch Analysis
For Example You are about to file a patent application ndash that contains
~ 300 ndash 400 chemical compounds How do you know if any
of these (400+) compounds has been patented before
Paste a list of InChIkeys to be batch searched here
Input list of InChIkeys to be batch searched here
1
2
Click run search
Results form batch search of InChikeys
Diavan Glipazol Ibuprofen Asprin Lotensin ImItrex Nabumetone Tessalon Sulfamethoxazole Trimethoprim Cyclobenzaprine Guaifenesin Oxymetazoline Anvitoff Dextromethorphan Lyrica Celexa
One can readily search hundreds or even thousands of compounds at at time ndash to see if any of the compounds have already been patented - amp by whom amp for what purpose
Exploring co-table analysis of Molecules with Gene IDrsquos
For example ndash show me all of the co-occurrences of these (x) molecules with these (any all) genersquos
From the main menu select the Analyze tab 1
2 From the analyze menu select the Cotable tab
3 Now Enter the Inchi keys for the molecules of interest -
Click here to enter a sample (test) set of molecules
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text [ Text + Annotations]
identify all targets [Gene names amp their synonyms ]
Augment all target names with a ldquotag = geneid ldquo amp the NCBI unique Identifier for that target
- - - - - - - - - - - - - - - - - - - -
Re-index the augmentented text + geneid identifiers w SOLR
= JAK3 + Aliases = geneid = geneid=NCBIID = 3718
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification for targets (=geneidrsquos)
Annotated Text Index
Add the derived annotations (amp meta data) to our master database
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text Text + Annotation
Identify all known MeSH terms [for example diseases (C01) or signs amp symptoms (C23)
Identified amp augment every occurrence of every MeSh term with a lsquotag = MeSH amp the specific MeSh code Identifier
- - - - - - - - - - - - - - - - - - - -
Re-index the augmented text + the MeSh tags w SOLR
= Headache + = MeSH term + = C23 sign or symptom
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification for MeSh terms
Text Index + Annotation Index
Text = Headache
New index of original text plus all of itrsquos associated annotated information
Add the derived annotations (amp meta data) to our master database
A Sample Augmented text
ldquoInteractions of ibogaine and D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] in vivo microdialysis and motor behavior in rats Ibogaine an indolalkylamine has been proposed for use in treating stimulant addiction In the present study we sought to determine if ibogaine had any effects on the neurochemical and motor changes induced by D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] that would substantiate the anti-addictive claim Ibogaine (40 mgkg ip) injected 19 h prior to a D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] challenge (125 mgkg ip) potentiated the expected rise in extracellular dopamine[ibmentity type=drug name=dopamine value=dopamine chebitype=pharmacological roleneurotransmitter agent] levels in the striatum[ibmentity type=target name=striatum value=striatum targettype=tissue] and in the nucleus accumbens as measured by microdialysis in freely moving rats Using helliprdquo
Examples - why this is important and what it enables us to do that we could not easily do before -
Batch Analysis
For Example You are about to file a patent application ndash that contains
~ 300 ndash 400 chemical compounds How do you know if any
of these (400+) compounds has been patented before
Paste a list of InChIkeys to be batch searched here
Input list of InChIkeys to be batch searched here
1
2
Click run search
Results form batch search of InChikeys
Diavan Glipazol Ibuprofen Asprin Lotensin ImItrex Nabumetone Tessalon Sulfamethoxazole Trimethoprim Cyclobenzaprine Guaifenesin Oxymetazoline Anvitoff Dextromethorphan Lyrica Celexa
One can readily search hundreds or even thousands of compounds at at time ndash to see if any of the compounds have already been patented - amp by whom amp for what purpose
Exploring co-table analysis of Molecules with Gene IDrsquos
For example ndash show me all of the co-occurrences of these (x) molecules with these (any all) genersquos
From the main menu select the Analyze tab 1
2 From the analyze menu select the Cotable tab
3 Now Enter the Inchi keys for the molecules of interest -
Click here to enter a sample (test) set of molecules
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
- - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - - -
= Chemical
= Target
= Disease
= Assay data
Text Text + Annotation
Identify all known MeSH terms [for example diseases (C01) or signs amp symptoms (C23)
Identified amp augment every occurrence of every MeSh term with a lsquotag = MeSH amp the specific MeSh code Identifier
- - - - - - - - - - - - - - - - - - - -
Re-index the augmented text + the MeSh tags w SOLR
= Headache + = MeSH term + = C23 sign or symptom
dB SOLR index
Current activity ldquoin linerdquo entity tagging amp classification for MeSh terms
Text Index + Annotation Index
Text = Headache
New index of original text plus all of itrsquos associated annotated information
Add the derived annotations (amp meta data) to our master database
A Sample Augmented text
ldquoInteractions of ibogaine and D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] in vivo microdialysis and motor behavior in rats Ibogaine an indolalkylamine has been proposed for use in treating stimulant addiction In the present study we sought to determine if ibogaine had any effects on the neurochemical and motor changes induced by D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] that would substantiate the anti-addictive claim Ibogaine (40 mgkg ip) injected 19 h prior to a D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] challenge (125 mgkg ip) potentiated the expected rise in extracellular dopamine[ibmentity type=drug name=dopamine value=dopamine chebitype=pharmacological roleneurotransmitter agent] levels in the striatum[ibmentity type=target name=striatum value=striatum targettype=tissue] and in the nucleus accumbens as measured by microdialysis in freely moving rats Using helliprdquo
Examples - why this is important and what it enables us to do that we could not easily do before -
Batch Analysis
For Example You are about to file a patent application ndash that contains
~ 300 ndash 400 chemical compounds How do you know if any
of these (400+) compounds has been patented before
Paste a list of InChIkeys to be batch searched here
Input list of InChIkeys to be batch searched here
1
2
Click run search
Results form batch search of InChikeys
Diavan Glipazol Ibuprofen Asprin Lotensin ImItrex Nabumetone Tessalon Sulfamethoxazole Trimethoprim Cyclobenzaprine Guaifenesin Oxymetazoline Anvitoff Dextromethorphan Lyrica Celexa
One can readily search hundreds or even thousands of compounds at at time ndash to see if any of the compounds have already been patented - amp by whom amp for what purpose
Exploring co-table analysis of Molecules with Gene IDrsquos
For example ndash show me all of the co-occurrences of these (x) molecules with these (any all) genersquos
From the main menu select the Analyze tab 1
2 From the analyze menu select the Cotable tab
3 Now Enter the Inchi keys for the molecules of interest -
Click here to enter a sample (test) set of molecules
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
A Sample Augmented text
ldquoInteractions of ibogaine and D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] in vivo microdialysis and motor behavior in rats Ibogaine an indolalkylamine has been proposed for use in treating stimulant addiction In the present study we sought to determine if ibogaine had any effects on the neurochemical and motor changes induced by D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] that would substantiate the anti-addictive claim Ibogaine (40 mgkg ip) injected 19 h prior to a D-amphetamine[ibmentity type=drug name=amphetamine value=amphetamine chebitype=neurotoxintoxin] challenge (125 mgkg ip) potentiated the expected rise in extracellular dopamine[ibmentity type=drug name=dopamine value=dopamine chebitype=pharmacological roleneurotransmitter agent] levels in the striatum[ibmentity type=target name=striatum value=striatum targettype=tissue] and in the nucleus accumbens as measured by microdialysis in freely moving rats Using helliprdquo
Examples - why this is important and what it enables us to do that we could not easily do before -
Batch Analysis
For Example You are about to file a patent application ndash that contains
~ 300 ndash 400 chemical compounds How do you know if any
of these (400+) compounds has been patented before
Paste a list of InChIkeys to be batch searched here
Input list of InChIkeys to be batch searched here
1
2
Click run search
Results form batch search of InChikeys
Diavan Glipazol Ibuprofen Asprin Lotensin ImItrex Nabumetone Tessalon Sulfamethoxazole Trimethoprim Cyclobenzaprine Guaifenesin Oxymetazoline Anvitoff Dextromethorphan Lyrica Celexa
One can readily search hundreds or even thousands of compounds at at time ndash to see if any of the compounds have already been patented - amp by whom amp for what purpose
Exploring co-table analysis of Molecules with Gene IDrsquos
For example ndash show me all of the co-occurrences of these (x) molecules with these (any all) genersquos
From the main menu select the Analyze tab 1
2 From the analyze menu select the Cotable tab
3 Now Enter the Inchi keys for the molecules of interest -
Click here to enter a sample (test) set of molecules
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
Examples - why this is important and what it enables us to do that we could not easily do before -
Batch Analysis
For Example You are about to file a patent application ndash that contains
~ 300 ndash 400 chemical compounds How do you know if any
of these (400+) compounds has been patented before
Paste a list of InChIkeys to be batch searched here
Input list of InChIkeys to be batch searched here
1
2
Click run search
Results form batch search of InChikeys
Diavan Glipazol Ibuprofen Asprin Lotensin ImItrex Nabumetone Tessalon Sulfamethoxazole Trimethoprim Cyclobenzaprine Guaifenesin Oxymetazoline Anvitoff Dextromethorphan Lyrica Celexa
One can readily search hundreds or even thousands of compounds at at time ndash to see if any of the compounds have already been patented - amp by whom amp for what purpose
Exploring co-table analysis of Molecules with Gene IDrsquos
For example ndash show me all of the co-occurrences of these (x) molecules with these (any all) genersquos
From the main menu select the Analyze tab 1
2 From the analyze menu select the Cotable tab
3 Now Enter the Inchi keys for the molecules of interest -
Click here to enter a sample (test) set of molecules
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
Batch Analysis
For Example You are about to file a patent application ndash that contains
~ 300 ndash 400 chemical compounds How do you know if any
of these (400+) compounds has been patented before
Paste a list of InChIkeys to be batch searched here
Input list of InChIkeys to be batch searched here
1
2
Click run search
Results form batch search of InChikeys
Diavan Glipazol Ibuprofen Asprin Lotensin ImItrex Nabumetone Tessalon Sulfamethoxazole Trimethoprim Cyclobenzaprine Guaifenesin Oxymetazoline Anvitoff Dextromethorphan Lyrica Celexa
One can readily search hundreds or even thousands of compounds at at time ndash to see if any of the compounds have already been patented - amp by whom amp for what purpose
Exploring co-table analysis of Molecules with Gene IDrsquos
For example ndash show me all of the co-occurrences of these (x) molecules with these (any all) genersquos
From the main menu select the Analyze tab 1
2 From the analyze menu select the Cotable tab
3 Now Enter the Inchi keys for the molecules of interest -
Click here to enter a sample (test) set of molecules
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
Paste a list of InChIkeys to be batch searched here
Input list of InChIkeys to be batch searched here
1
2
Click run search
Results form batch search of InChikeys
Diavan Glipazol Ibuprofen Asprin Lotensin ImItrex Nabumetone Tessalon Sulfamethoxazole Trimethoprim Cyclobenzaprine Guaifenesin Oxymetazoline Anvitoff Dextromethorphan Lyrica Celexa
One can readily search hundreds or even thousands of compounds at at time ndash to see if any of the compounds have already been patented - amp by whom amp for what purpose
Exploring co-table analysis of Molecules with Gene IDrsquos
For example ndash show me all of the co-occurrences of these (x) molecules with these (any all) genersquos
From the main menu select the Analyze tab 1
2 From the analyze menu select the Cotable tab
3 Now Enter the Inchi keys for the molecules of interest -
Click here to enter a sample (test) set of molecules
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
Input list of InChIkeys to be batch searched here
1
2
Click run search
Results form batch search of InChikeys
Diavan Glipazol Ibuprofen Asprin Lotensin ImItrex Nabumetone Tessalon Sulfamethoxazole Trimethoprim Cyclobenzaprine Guaifenesin Oxymetazoline Anvitoff Dextromethorphan Lyrica Celexa
One can readily search hundreds or even thousands of compounds at at time ndash to see if any of the compounds have already been patented - amp by whom amp for what purpose
Exploring co-table analysis of Molecules with Gene IDrsquos
For example ndash show me all of the co-occurrences of these (x) molecules with these (any all) genersquos
From the main menu select the Analyze tab 1
2 From the analyze menu select the Cotable tab
3 Now Enter the Inchi keys for the molecules of interest -
Click here to enter a sample (test) set of molecules
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
Results form batch search of InChikeys
Diavan Glipazol Ibuprofen Asprin Lotensin ImItrex Nabumetone Tessalon Sulfamethoxazole Trimethoprim Cyclobenzaprine Guaifenesin Oxymetazoline Anvitoff Dextromethorphan Lyrica Celexa
One can readily search hundreds or even thousands of compounds at at time ndash to see if any of the compounds have already been patented - amp by whom amp for what purpose
Exploring co-table analysis of Molecules with Gene IDrsquos
For example ndash show me all of the co-occurrences of these (x) molecules with these (any all) genersquos
From the main menu select the Analyze tab 1
2 From the analyze menu select the Cotable tab
3 Now Enter the Inchi keys for the molecules of interest -
Click here to enter a sample (test) set of molecules
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
Exploring co-table analysis of Molecules with Gene IDrsquos
For example ndash show me all of the co-occurrences of these (x) molecules with these (any all) genersquos
From the main menu select the Analyze tab 1
2 From the analyze menu select the Cotable tab
3 Now Enter the Inchi keys for the molecules of interest -
Click here to enter a sample (test) set of molecules
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
From the main menu select the Analyze tab 1
2 From the analyze menu select the Cotable tab
3 Now Enter the Inchi keys for the molecules of interest -
Click here to enter a sample (test) set of molecules
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
2 From the analyze menu select the Cotable tab
3 Now Enter the Inchi keys for the molecules of interest -
Click here to enter a sample (test) set of molecules
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
3 Now Enter the Inchi keys for the molecules of interest -
Click here to enter a sample (test) set of molecules
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
4 Now select - patent field ndash to explore ldquopatentsrdquo
These are the molecules of interest ndash (Inchi keys to explore)
Select Patent field here
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
5 Now select - facet = patent field + Gene then click analyze
Molecules
Facet = Patents + Genes
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
These are the NCBI Gene ID rsquos
To transpose the charts or export the data ndash click here
This shows the ldquocotablerdquo results = co-occurrences of molecules + NCBI ndashGene IDrsquos
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
This shows the transposed chart ndash of co-occurrences of molecules + NCBI ndashGene IDrsquos
Click here to see the patents containing this molecule + this particular gene
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
Co-table Analysis
For example Show me all documents where imitrex was
Mentioned with ldquoanyrdquo hellipsign and or symptoms
(note these are terms such as headache vomiting nausea
etc there are gt 680 of them)
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
Draw a compound of interest 1
2
Click ndash view compound in co-table
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
Draw a compound of interest 1
2
Click ndash view compound in co-table ChemAxon
Marvin [Name= Structure]
Chem Libraries J Chem Base
Chemical Search
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
3 Select a MeSH category for Co-occurance analysis
4 Click analyze
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash C23 terms
Click on the numbers to ldquolink to rdquo the documents
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
Type in a new MeSH code to change the analysis from lsquosigns amp symptomsrsquo (C23) to diseases (C01)
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
This shows the number of documents that contained the source molecule and ANY of the MeSH ndash disease (C01) terms
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
This shows the comparison of 2 drugs and the co-occurrence of MeSH Symptoms (C23) terms
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
Medline co-occurrence of Statin structures vs MeSH ndash
Chemical Structures vs Signs and Symptoms
This shows the comparison of different statins and the co-occurrence of MeSh terms
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
Dat
a So
urc
es
View selected
Documents amp Reports
US Patents (1976 -mdash
2009)
US Pre-
Grants (All)
PCT amp EPO Apps
Medline Abstracts
(gt18 M)
Selected Internet Content
User Applications
In-House
Content
Knime or Pipeline Pilot
BIW
SIMPLE
Chem Axon Search
CognosDDQB Other Apps
Parse amp Extract
data
Annotator 1
Annotator 2
Database
+ compu ted Meta Data
e Classifier amp Other Data Associations
Annotation Factory
Computational Analytics
(Semantic
Associations)
Computer Curation Process Overview amp integration with our collaborators -
IP Database (eg DB2)
ADU
ADU = Automated Data Update
ChemVerse
db
ChemVerse
Services Hosted at IBM Almaden
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
Screen shoots from our SIMPLE SIIP Web application
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
Search Chemical Search using ChemAxon w DB2
Proximal Search Nearest Neighbor Search
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
BioTerm Analysis
Clustering Claims Originality
Discovery
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
Landscape Analysis
Visualization
Networks
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -
I would like to acknowledge the IBM Almaden Research ndash team
Jeff Kreulen
Ying Chen Scott Spangler Alfredo Alba Tom Griffin Eric Louie Su Yan Issic Cheng Prasad Ramachandran Bin He Ana Lelescu
Qi He Linda Kato Ana Lelescu Brad Wade John Colino Meenakshi Nagarajan Timothy J Bethea German Attanasio Laura Anderson Robert Prill + a host of folks from IBM China Labs -