swanson rfo-pres-grp-mtg

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A Graph-Based Decomposition of Swanson’s Hypothesis using Semantic Predications Delroy Cameron, Olivier Bodenreider, Hima Yalamanchili, Tu Danh, Sreeram Vallabhaneni, Krishnaprasad Thirunarayan, Amit P. Sheth and Thomas C. Rindflesch 02/17/2012

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Presentation to Kno.e.sis group on graph-based techniques for decomposing Swanson's RS-DFO Hypothesis

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Page 1: Swanson rfo-pres-grp-mtg

A Graph-Based Decomposition of Swanson’s Hypothesis using

Semantic Predications

Delroy Cameron, Olivier Bodenreider, Hima Yalamanchili, Tu Danh, Sreeram Vallabhaneni, Krishnaprasad Thirunarayan,

Amit P. Sheth and Thomas C. Rindflesch

02/17/2012

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OUTLINEBackground

Swanson’s HypothesisLiterature-Based Discovery (LBD)

Problem

Graph-based Approach

Experimental Results

Future Work

Conclusion

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SWANSON’S HYPOTHESIS

Source: http://academic.research.microsoft.com/VisualExplorer#185977

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SWANSON’S HYPOTHESISRaynaud Syndrome – Fish Oil Hypothesis

(1986)1

Scientific Literatureest. 1000 Fish Oil articlesest. 2000 Raynaud articles

FeaturesFew co-referencesOverlapping terms/concepts

“dietary fish oil might prevent Raynaud’s syndrome.”

2 relevant articles, S. Moncada

63 relevant papers

25 DFO 34 RS4

489 Medline + Embase

4

DFO RS

1Swanson D. Fish oil, raynaud’s syndrome, and undiscovered public knowledge. Perspect Biol Med 1986;30(1):7–18.

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SWANSON’S HYPOTHESIS

Platelet Aggregatio

n

DFOBlood

ViscosityRaynaud

Syndrome

Vascular Reactivity

“dietary fish oil might prevent Raynaud’s syndrome.”

INHIBITS

INHIBITS

INHIBITS

CAUSES

CAUSES

CAUSES

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LITERATURE-BASED DISCOVERY(LBD)

Finding explicit connectionsUndiscovered public knowledge2

Noninteracting literatures

ABC Model

2Swanson DR.Undiscovered public knowledge.Library Quarterly 1986;56(1):103–18.

A B C

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PROBLEMIR-based techniques

Lack context

ABC ModelLack coverageAnC3 Model, n={B1, B2…Bm}

3Wilkowski B, Fiszman M, Miller C, Hristovski D, Arabandi S, Rosemblat G, Rindflesch T. Discovery browsing with semantic predications and graph theory. AMIA Annu Symp Proc 2011

DFO

Platelet Aggregatio

n

RaynaudSyndro

meINHIBITS CAUSE

S

Epoprostenol

Prostaglandin

STIMULATES ISA

INHIBITS

A C

B1

B2

B3B

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PROBLEM-SOLUTION AnC Model

Multiple Paths3

Subgraphs3

Background knowledge*

DFO

RaynaudSyndromeTREATS

Epoprostenol

STIMULATES

DFO

Platelet Aggregatio

n

RaynaudSyndrom

e

INHIBITS

CAUSES

Prostaglandin

PRODUCES

ISASTIMULATES TREATS

3Wilkowski B, Fiszman M, Miller C, Hristovski D, Arabandi S, Rosemblat G, Rindflesch T. Discovery browsing with semantic predications and graph theory. AMIA Annu Symp Proc 2011

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CONTRIBUTIONGraph-based Framework for LBD

Semantic predications From ABC Model to AnC Model Construct expressive subgraphs Background knowledge*

Evaluate/Assess Recover Swanson’s Hypothesis Decompose Swanson’s Hypothesis*

Question Answering

Information Retrieval

Literature-based Discovery

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ABC Mode

l

AnC Mode

l

Graph Theor

y

Subgraphs

Background

knowledge

Hristovski [14,15,26] (BITOLA)

✔ ✔

Pratt [13, 22](LitLinker)

✔ ✔

Ahlers [16] ✔

Cohen [23](Epiphanet)

✔ ✔

Wilkowski [17] ✔ ✔ ✔

Cameron* ✔ ✔ ✔ ✔

RELATED WORK (Semantics-based)

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IMPACTInterdisciplinary Research

Mechanisms of operationCausality Relationships

Semantic Integration of Heterogeneous DataExperimental DataScientific LiteratureStructured Data

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1. Literature Preprocessing

2. Predication Extraction (SemRep)

3. Predications Graph Creation

4. Path generation Extend ABC Model to AnC Model

5. Subgraph Construction Multiple Paths Background Knowledge

APPROACH

Path Generation

Corpus

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RS

Path GenerationReachability

“the notion of being able to get from one vertex in a directed graph to some other vertex”

A

C

DFO ReachabilityRelation

Transitive Closure =

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Subgraph CreationOriginal Swanson Associations

Thoroughly read Paper1

Three (3) Primary Associationso Eight (8) Supplementary Associationso Eight (8) Secondary Associations

Subgraph Construction (manual)Classifying Paths from Reachability RelationHuman Cognition as Background Knowledge

1Swanson D. Fish oil, raynaud’s syndrome, and undiscovered public knowledge. Perspect Biol Med 1986;30(1):7–18.

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Primary/Supplementary Associations

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Dataset & ExperimentsExperiment I

Baseline1: Full Text (Titles, Abstracts, Text)

Experiment IIBaseline2: Titles, Abstracts

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Experiments

Reachability Relation= 36 paths

Reachability Relation= 146 paths

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Platelet Aggregation (path#1) Primary

Dietary Fish Oil->INHIBITS->platelet aggregation->CAUSES->Raynaud Syndrome

Epoprostenol

Raynaud Syndrome

DISRUPTS

DISRUPTS

Platelet AggregationDFO CAUSES

STIMULATES TREATS

Four Relevant Paths

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Platelet Aggregation (path#2) Supplementary

DFO

Dietary Fish Oil->PRODUCES->Prostaglandin (PGI3)-> INHIBITS->platelet aggregation->CAUSES->Raynaud Syndrome

Epoprostenol

Raynaud Syndrome

Platelet Aggregation

Prostaglandin I3

ISA

CONVERTS_TO

DISRUPTS CAUSES

Prostaglandin

ISACONVERTS_TO

DISRUPTS

DISRUPTS

STIMULATES TREATS

DISRUPTS

Eight Relevant Paths

TREATS

TREATS

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Platelet Aggregation (path#3) PrimaryDietary Fish Oil->INHIBITS->Blood Viscosity->CAUSES ->Raynaud Syndrome

Raynaud Syndrome

Ketanserin

TREATSDISRUPTS

Epoprostenol

TREATS

Blood Viscosity

DISRUPTS

STIMULATES DISRUPTS

CAUSESDFO

Four Relevant Paths

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Platelet Aggregation (path#4) SupplementaryDietary Fish Oil->INHIBITS->triglyceride->ISA->Blood Lipid->AFFECTS->Blood Viscosity->CAUSES ->Raynaud Syndrome

Raynaud SyndromeDFO Blood

ViscosityDISRUPTS CAUSES

Fatty Acid

ISA

Essential Fatty Acid

ISA

Triglyceride

INHIBIT

AFFECTS

Lipid

ISA

Six Relevant Paths

INHIBITS

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Experimental Results

Association Type

Experiment I Experiment II

Primary (3) 3 2* (1VR missing)

Supplementary (8)

4 (2VR, 2BV missing)

4* (2VR, 2BV missing)

Secondary (8) 7 (1VR missing) 5* (3VR missing)

* - Not sufficiently detailed

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ABC Mode

l

AnC Mode

l

Graph Theor

y

Subgraphs

Background

knowledge

Hristovski [14,15,26] (BITOLA)

✔ ✔

Pratt [13, 22](LitLinker)

✔ ✔

Ahlers [16] ✔

Cohen [23](Epiphanet)

✔ ✔

Wilkowski [17] ✔ ✔ ✔

Cameron* ✔ ✔ ✔ ✔

RELATED WORK (Semantics-based)

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FUTURE WORKScalability

Path Clusteringo Structural Features (Centrality, Geodesic)o Semantic Features (Similarity, Relatedness)

Semantic Integration of Background Knowledge

o Heuristics (knowledge abstraction,[CameronBIBM2011])

Inconsistencies

Predication Extraction (SemRep)

Corpus (Richness)

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CONCLUSIONGraph-based Framework (GFB) for

LBDSemantic predicationsExtend ABC Model to AnC ModelConstruct expressive subgraphsBackground knowledge*

Evaluate/AssessRecover Swanson’s HypothesisDecompose Swanson’s Hypothesis*

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The future of LBD requires the

Semantic Integration of

subgraphs and background knowledge

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POTENTIAL DISCOVERY

Raynaud Syndrome

AspirinEpoproste

nolINHIBITS TREATS

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QUESTIONS