application of compute science in tics

8/4/2019 Application of Compute Science in tics

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CIS427: Introduction to

BioinformaticsThe application of computer science in

Bioinformatics

Dr V. C. Osamor

Department of Computer & Information Science(Bioinformatics unit)Covenant University

[email protected]

Dr V.C. Osamor CIS427


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Objectives

To expose the students to possible areasof computer techniques applicable inBioinformatics.

To expose students to how prediction isimportant in solving Biology problem.

To expose students to how machine

learning is applicable in BioinformaticsTo expose students to how Expert Systemis applicable in Bioinformatics.



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The prediction Problem

Make any sentence from English language

We know that letters do not occur in English at random(e.g. e is more common than z)

Predicting symbols is fundamental to a wide range ofimportant applications (e.g. encryption, compression)



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Prediction in bioinformatics

This will largely require development of your own

computational tools or the use of existing tools inareas such as:

Predicting the location of genes in DNA

Predicting gene roles in an organismPredicting errors in a genetic transcription

Predicting the function of proteins

Predicting diseases from molecular samplesAnything that involves making a judgment; a

yes/no decision about whether some sampledatum does or does not have some property.



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Representation

DATA - DATA

0101011101100101011001010111010000101101

to the computer, everything is binary!



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0101011101100101011001010111010000101101

0101101100100111111011010011010000101101

A A C G T C A T T C G A T G A T T C G A

Just as we can teach a computer to predictthings about a sequence of letters in Englishprose, we can also teach it to predict thingsabout other sequenceslike a genetic

sequence



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A genetic prediction problem

ttgcaatcggcgctacgcttcaaaatttattatattcccggcgcggctacgttcatcccagcagcagcgattttaaaattaacgcatcagactctcgtcgcgttcgtcgcctttattcacgcta

atggacgacatcttttactacgacggcgcctacgcatcgcagcatacgacgcccagcatagtattttagaggcgaggacatcatcatatcgcagctacagcgcatcagacgcata

cgacgacgactacgacgacactaacgacgatgttgcgcacccacaccagttatatagagacgaactcgcatcagc



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ttgcaatcggcgctacgcttcaaaatttattatattcccggcgcggctacgttcatcccagcagcagcgattttaaaattaacgcatcagactctcgtcgcgttcgtcgcctttattcacgctaatggacgacatcttttactacgacggcgcctacgcatcgcagcatacgacgcccagcatagtattttagaggcgaggacatcatcatatcgcagctacagcgcatcagacgcatacgacgacgactacgacgacactaacgacgatgttgcgcacccacaccagttatatagagacgaactcgcatcagctgcaatcggcgctacgcttcaaaatttattatattcccggcgcggctacgttcatcccagcagcagcgattttaaaattaacgcatcagactctcgtcgcgttcgtcgcctttattcacgctaatggacgacatcttttactacgacggcgcctacgcatcgcagcatacgacgcccagcatagtattttagaggcgaggacatcatcatatcgcagctacagcgcatcagacgcatacgacgacgactacgacgacactaacgacgatgttgcgcacccacaccagttatatagagacgaactcgcatcagtgcaatcggcgctacgcttcaaaatttattatattcccggcgcggctacgttcatcccagcagcagcgattttaaaattaacgcatcagactctcgtcgcgttcgtcgcctttattcacgctaatggacgacatcttttactacgacggcgcctacgcatcgcagcatacgacgcccagcatagtattttagaggcgaggacatcatcatatcgcagctacag

cgcatcagacgcatacgacgacgactacgacgacactaacgacgatgttgcgcacccacaccagttatatagagacgaactcgcatcagtgcaatcggcgctacgcttcaaaatttattatattcccggcgcggctacgttcatcccagcagcagcgattttaaaattaacgcatcagactctcgtcgcgttcgtcgcctttattcacgctaatggacgacatcttttactacgacggcgcctacgcatcgcagcatacgacgcccagcatagtattttagaggcgaggacatcatcatatcgcagctacagcgcatcagacgcatacgacgacgactacgacgacactaacgacgatgttgcgcacccacaccagttatatagagacgaactcgcatcagtgcaatcggcgctacgcttcaaaatttattatattcccggcgcggctacgttcatcccagcagcagcgattttaaaattaacgcatcagactctcgtcgcgttcgtcgcctttattcacgctaatggacgacatcttttactacgacggcgcctacgcatcgcagcatacgacgcccagcatagtattttagaggcgaggacatcatcatatcgcagctacagcgcatcagacgcatacgacgacgactacgacgacactaacgacgatgttgcgcacccacaccagttatatagagacgaactcgcatcagtgcaatcggcgctacgcttcaaaatttattatattcccggcgcggctacgttcatcccagcagcagcgattttaaaattaacgcatcagactctcgtcgcgttcgtcgcctttattcacgctaatggacgacatcttttactacgacggcgcctacgcatcgcagcatacgacgcccagcatagtattttagaggcgaggacatcatcatatcgcagctacagcgcatcagacgcat

acgacgacgactacgacgacactaacgacgatgttgcgcacccacaccagttatatagagacgaactcgcatcagtgcaatcggcgctacgcttcaaaatttattatattcccggcgcggctacgttcatcccagcagcagcgattttaaaattaacgcatcagactctcgtcgcgttcgtcgcctttattcacgctaatggacgacatcttttactacgacggcgcctacgcatcgcagcatacgacgcccagcatagtattttagaggcgaggacatcatcatatcgcagctacagcgcatcagacgcatacgacgacgactacgacgacactaacgacgatgttgcgcacccacaccagttatatagagacgaactcgcatcagtgcaatcggcgctacgcttcaaaatttattatattcccggcgcggctacgttcatcccagcagcagcgattttaaaattaacgcatcagactctcgtcgcgttcgtcgcctttattcacgctaatggacgacatcttttactacgacggcgcctacgcatcgcagcatacgacgcccagcatagtattttagaggcgaggacatcatcatatcgcagctacagcgcatcagacgcatacgacgacgactacgacgacactaacgacgatgttgcgcacccacaccagttatatagagacgaactcgcatcagtgttgcgcacccacaccagttatatagagacgaactc



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A gene encodes a protein

It is a blueprint that provides biochemicalinstructions on how to construct a sequence ofamino acids so as to make a working proteinthat will perform some function in the organism



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encoding regionuntranslated region

transcription

factor RNARNA

RNA

RDr V.C. Osamor CIS427


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untranslated regionttgcaatcggcgctacgcttcaaaatttattatattcccggc



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ttgcaatcggcgctacgcttcaaaatttattatattcccggc

What transcription factors bind to this gene?

Where is the transcription factor binding site?



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Clues: A binding site is often a short general pattern

E.g. CCGATNATCGG



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Clues: The patterns are often reverse complements

E.g. CCGATNATCGGGGCTANTAGCC



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Clues: Where there is one binding site, often there is

another nearby.



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A genetic prediction problem-ALGORITHMS and DATA

STRUCTURES

All of these properties are the kinds of things forwhich computer science has developedalgorithms and data structures to identify quicklyand efficiently, and therefore it is exactly the

kind of problem computer scientists should beable to solve.



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Proteomics

Three consecutive nucleotides in the coding regionform a codon i.e. encode an amino acid.

A string of amino acids makes a protein.

3 nucleotides, 4 possibilities each: ACTG

43

= 64 possible codons

But there are only 20 amino acids!



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proteomics

Glycine: GGA, GGC, GGG, GGTTyrosine: TAT, TACMethionine: ATG

There is quite a bit of redundancy in codons.



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Amidegroup

Carboxylgroup

R group

Amino Acid



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Amino Acid

glycine

tyrosine



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Artificial Intelligence

Computers do thingsonly human brainscan otherwise do

expertsystem

expert



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Artificial Intelligence & MachineLearning

Computers do thingsonly human brainscan otherwise do

learningsystem

expertsystem



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Machine learning

creating computer programs that get better with experiencelearn how to make expert judgmentsdiscover previously hidden, potentially useful information (data

mining)

What is machine learning?

How does it work?

user provides learning system with examples of concept to belearned

induction algorithm infers a characteristic model of the examplesmodel is used to predict whether or not future novel instances arealso examples and it does this very consistently, and very, veryquickly!



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Statistical and Mathematicaltechniques

Statistical and mathematical techniques,ranging from exact, heuristics, fixedparameter and approximation algorithms

for problems based on parsimony models

To Markov Chain Monte Carlo algorithms

for Bayesian analysis of problems basedon probabilistic models.

http://en.wikipedia.org/wiki/Heuristicshttp://en.wikipedia.org/wiki/Approximation_algorithmshttp://en.wikipedia.org/wiki/Markov_Chain_Monte_Carlohttp://en.wikipedia.org/wiki/Bayesian_analysishttp://en.wikipedia.org/wiki/Bayesian_analysishttp://en.wikipedia.org/wiki/Markov_Chain_Monte_Carlohttp://en.wikipedia.org/wiki/Approximation_algorithmshttp://en.wikipedia.org/wiki/Heuristics


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OTHER BIOINFORMATICSAPPLICATIONS



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Bioinformatics Applications

Bioinformatics was applied in the creation andmaintenance of a database to store biologicalinformation at the beginning of the "genomicrevolution", such as nucleotide and amino acidsequences.

Development of this type of database involvednot only design issues but the development ofcomplex interfaces whereby researchers couldboth access existing data as well as submit newor revised data.



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Biotechnology

Biologists know proteins, computerscientists know machine learning

Together, they can find out a lot of hiddeninformation about genes and proteins

Biotechnology is a multi-billion dollarindustry

Biotechnology is one of the best fundedareas of scientific research



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Modelling a Biological system

There are two fundamental ways of modelling aBiological system (e.g. living cell) both comingunder Bioinformatic approaches.

Static Sequences - Proteins, Nucleic acids and Peptides

Structures - Proteins, Nucleic acids, Ligands(including metabolites and drugs) and Peptides

Interaction data among the above entities includingmicroarray data and Networks of proteins,metabolites



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Modelling Biological System

Dynamic

Systems Biology comes under this categoryincluding reaction fluxes and variable

concentrations of metabolites Multi-Agent Based modelling approaches

capturing cellular events such as signalling,transcription and reaction dynamics



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Major Research Efforts

Major research efforts in the field includesequence alignment, gene finding, genomeassembly,

drug design, drug discovery, protein structurealignment, protein structure prediction,

prediction of gene expression and protein-

protein interactions,genome-wide association studies

and the modeling of evolution.


a or researc areas
http://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformatics


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a or researc areas 1 Sequence analysis

2 Genome annotation

3 Computational evolutionary biology

4 Analysis of gene expression

5 Analysis of regulation

6 Analysis of protein expression 7 Analysis of mutations in cancer

8 Comparative genomics

9 Modeling biological systems 10 High-throughput image analysis 11 Structural Bioinformatic Approaches

- Prediction of protein structure, Molecular Interaction ,Docking algorithms


S A l i
http://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformatics


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Sequence AnalysisThis sequence information is analyzed to

determine genes that encode polypeptides(proteins), RNA genes, regulatory sequences,structural motifs, and repetitive sequences.

A comparison of genes within a species orbetween different species can show similaritiesbetween species (the use of molecularsystematics to construct phylogenetic trees).

With the growing amount of data, it becameimpractical to analyze DNA sequencesmanually. Today, computer programs such as

BLAST are used. Dr V.C. Osamor CIS427

Genome Annotation/Gene finding
http://en.wikipedia.org/wiki/Specieshttp://en.wikipedia.org/wiki/Molecular_systematicshttp://en.wikipedia.org/wiki/Molecular_systematicshttp://en.wikipedia.org/wiki/Phylogenetic_treehttp://en.wikipedia.org/wiki/Computer_programhttp://en.wikipedia.org/wiki/BLASThttp://en.wikipedia.org/wiki/BLASThttp://en.wikipedia.org/wiki/Computer_programhttp://en.wikipedia.org/wiki/Phylogenetic_treehttp://en.wikipedia.org/wiki/Phylogenetic_treehttp://en.wikipedia.org/wiki/Phylogenetic_treehttp://en.wikipedia.org/wiki/Molecular_systematicshttp://en.wikipedia.org/wiki/Molecular_systematicshttp://en.wikipedia.org/wiki/Species


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Genome Annotation/Gene findingAnnotation is the process of marking the genesand other biological features in a DNA

sequence. The first genome annotationsoftware system was designed in 1995 by Dr.Owen White, who was part of the team at The

Institute for Genomic Research that sequencedand analyzed a free-living organism thebacterium Haemophilus influenzae.

He built a software system to find the genes(places in the DNA sequence that encode aprotein), the transfer RNA, and other features,and to make initial assignments of function tothose enes. Dr V.C. Osamor CIS427
http://en.wikipedia.org/wiki/Genome_projecthttp://en.wikipedia.org/wiki/The_Institute_for_Genomic_Researchhttp://en.wikipedia.org/wiki/The_Institute_for_Genomic_Researchhttp://en.wikipedia.org/wiki/Haemophilus_influenzaehttp://en.wikipedia.org/wiki/Haemophilus_influenzaehttp://en.wikipedia.org/wiki/Haemophilus_influenzaehttp://en.wikipedia.org/wiki/Haemophilus_influenzaehttp://en.wikipedia.org/wiki/The_Institute_for_Genomic_Researchhttp://en.wikipedia.org/wiki/The_Institute_for_Genomic_Researchhttp://en.wikipedia.org/wiki/Genome_project


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Computational Evolutionary Bio

Evolutionary biology is the study of theorigin and descent of species, as well astheir change over time. Informatics hasassisted evolutionary biologists in severalkey ways; it has enabled researchers to:

Trace the evolution

Compare GenomesComputational prediction model ofpopulation over time

http://en.wikipedia.org/wiki/Evolutionary_biologyhttp://en.wikipedia.org/wiki/Specieshttp://en.wikipedia.org/wiki/Informatics_%28academic_field%29http://en.wikipedia.org/wiki/Informatics_%28academic_field%29http://en.wikipedia.org/wiki/Specieshttp://en.wikipedia.org/wiki/Evolutionary_biology


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Comparative Genomics

The core of comparative genome analysisis the establishment of thecorrespondence between genes (orthology

analysis) or other genomic features indifferent organisms.



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High throughput Imaging

Image analysis systems augment anobserver's ability to make measurementsfrom complex set of images, by improving

accuracy, objectivity, or speed. Biomedicalimaging is becoming more important forboth diagnostics and research.
http://en.wikipedia.org/wiki/Accuracyhttp://en.wikipedia.org/wiki/Objectivity_%28science%29http://en.wikipedia.org/wiki/Diagnosticshttp://en.wikipedia.org/wiki/Diagnosticshttp://en.wikipedia.org/wiki/Objectivity_%28science%29http://en.wikipedia.org/wiki/Accuracy

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