An overview of Bioinformatics. Cell and Central Dogma.

An overview of

Bioinformatics

Cell and Central Dogma

Source: “Post-genome Informatics” by M Kanehisa

Source: “Post-genome Informatics” by M Kanehisa

Deduction and Analogy

Biological System(Organism)

Reductionistic SyntheticApproach Approach

(Experiments) (Bioinformatics)

Building Blocks(Genes/Molecules)

Source: “Post-genome Informatics” by M Kanehisa

Principles Known

Physics Chemistry Biology

Matter Compound Organism

Elementary Elements GenesParticles

Yes Yes No

Source: “Post-genome Informatics” by M Kanehisa

Searching and learning problems in biologyMethods in Informatics

Pairwise sequence alignment Optimization algorithms

Database search for similar sequences -Dynamic programmingMultiple sequence alignment -Simulated annealing

Phylogenetic tree reconstruction -Genetic alogrithmProtein 3D structure alignment -Hopfield neural network

RNA secondary structure prediction -Gibbs samplingRNA 3D structure prediction -Monte Carlo

Protein 3D sturcture prediction

Motif extraction Pattern recognition and learning algorithmFunctional site prediction -Discriminant analysisCellular localization prediction -Heirarchical neural networkCoding region prediction -Hidden Markov Model

Transmembrane segment prediction -Formal Grammar

Protein secondary structure prediction

Protein 3D sturcture predictionSuperfamily classification Clustering algorithm

Ortholog/paralog grouping of genes -Heirarchical cluster analysis

3D fold classification -Kohonen neural network

Gene Expression Clustering -Self Organization Map3D fold classification -Kohonen neural networkNetwork comparison -Graph theoryPathway construction -Network theoryDynamic analysis of network -Control theoryControl and design of system -System theory

Interaction and Pathway

Problems in Biology

Similarity search

Molecular classificatoin

Structure/function

prediction

ab initioprediction

Knowledgebased

prediction

Source: “Post-genome Informatics” by M Kanehisa

Sequence Comparison: Sequence Comparison: Algorithms and ApproachesAlgorithms and Approaches

Homology Search

New sequence

Similar sequences

Expert knowledge

Sequence interpretation

Sequence database(Primary data)

retrieval

Source: “Post-genome Informatics” by M Kanehisa

Pairwise sequence alignment by dynamic programming

Needleman Wunsch alogrithmSource: “Post-genome Informatics” by M Kanehisa

Database Search

for Similar Sequencesfor Similar Sequences

Web LabWeb Lab

MotifMotif

Source: “Introduction to Protein Structure” by Branden & Tooze

Web LabWeb Lab

Motif Search

New sequence Expert knowledge

Sequence interpretation

Sequence database(Primary data)

Motif library(Empirical rules)

inference

Source: “Post-genome Informatics” by M Kanehisa

Introduction toIntroduction to

Structural BiologyStructural Biology

Source: “Introduction to Protein Structure” by Branden & Tooze

Source: “Introduction to Protein Structure” by Branden & Tooze

Web LabWeb Lab

Web LabWeb Lab

Web LabWeb Lab

Genome ProjectGenome Project

Web LabWeb Lab

Genome SequencingGenome Sequencing

and and

Genome AnnotationGenome Annotation

A general model of the structure of genomic sequences

Source

: “Bio

info

rmatics” b

y D

W M

ount

MicroarrayMicroarray

Joe Sutliff for Science 291 p1224 (2001)

What kind of solution Genomics can provide with ? High Throughput Gene Discovery

165 genes are up-regulated in 75% tumors(MAPK pathway, APC, promotion of mitosis; 69 unknown)

170 genes are down-regulated in 65% tumors (hepatocyte-specific gene products, retinoid metabolism; 75 unknown)

Hierarchical ClusteringK-meansSelf Organization MapSupport Vector Single Value Decomposition

Gene Expression Gene Expression

andand

TranscriptomeTranscriptome

Web LabWeb Lab

Proteomics Proteomics

and and

Functional GenomicsFunctional Genomics

Source: “Post-genome Informatics” by M Kanehisa

Web LabWeb Lab

Integrative GenomicsIntegrative Genomics

Network of physical interactions between nuclear proteins

Attributes of generic network structures

Virtual Cell

Living Cell

PerturbationEnvironmental changeGene disruptionGene overexpression

Dynamic ResponseChanges in:Gene expression profiles,Etc.

BiologicalKnowledgeMolecular and CellularBiology,Biochemistry,Genetics, etc

Basic PrinciplesPractical Applications

Complete Genome Sequences

Source: “Post-genome Informatics” by M Kanehisa

Take Home Message

Define the biological problem.

Why is bioinformatics important ?A synthesis approach.

Prediction is a dangerous game. Always try your best to validate in the bench side.

The devil is in the detail. Always try different bioinformatic tools and databases.

Your knowledge rests on your own practice.

Reference Books you will find useful:

Bioinformatics -sequence and genome analysis by D W Mount

Introduction to Bioinformatics by A M Lesk

Post-genome Informatics by M Kanehisa

Evolution of molecular biology databases

Database category Data content Examples

1. Literature database Bibliographic citations MEDLINE(1971)On-line journals

2. Factual Database Nucleic acid sequences GenBank(1982)Amino acid sequences EMBL(1982)3D molecular structures DDBJ(1984)

SWISS_PROT(1986)PDB(1971)

3. Knowledge base Motif libraries PROSITE(1988)Molecular classification SCOP(1994)Biochemical pathways KEGG(1995)