Bio-bio-1 TeamAdvisor:

Dr. Supten Sarbadhikari

Members:

Fokhruz ZamanZohirul Alam TiemoonSaddam HossainFarjana Khatun

Bioinformatics

2 (c) Mark Gerstein, 1999, Yale, bioinfo.mbb.yale.edu

Original definition (1979 by Paulien Hogeweg):“application of information technology and computer science to the field of molecular biology”

Biological Data + Computational

Calculation

Derivation:Bio + InformaticsBio Bios (Greek) Life Informatics Informatique (French)

Data Processing

Why Use of BioinformaticsWhy bioinformaticsTo Find an answer quickly

- in-silicobiology is faster than in-vitroMassive amounts of data to analyse

• Need to make use of all information• Not possible to do analysis by hand• Can’t organise and store information only using lab

note books• Automation is key

All results of computer analysis should to be verified by biologists

Data Type Data Size Topics

Raw DNA sequence

8.2 million sequences(9.5 billion bases)

Separating coding and non-coding regionsIdentification of introns and exonsGene product predictionForensic analysis

Protein sequence

300,000 sequences(~300 amino acidseach)

Sequence comparison algorithmsMultiple sequence alignments algorithmsIdentification of conserved sequence motifs

Macromolecularstructure

13,000 structures(~1,000 atomiccoordinates each)

Secondary, tertiary structure prediction3D structural alignment algorithmsProtein geometry measurementsSurface and volume shape calculationsIntermolecular interactions

Data Type Data Size Topics

Genomes 40 complete genomes(1.6 million –3 billion bases each)

Characterisation of repeatsStructural assignments to genesPhylogenetic analysisGenomic-scale censuses(characterisation of protein content, metabolic pathways)Linkage analysis relating specific genes to diseases

Gene expression

largest: ~20 timepoint measurementsfor ~6,000 genes

Correlating expression patternsMapping expression data to sequence, structural andbiochemical data

Quantity of each type of data that is currently (August 2000) available

Why Use of BioinformaticsBiological data are being produced at a unusual

rate. On average, these databases are doubling in size

every 15 months To bring together and store vast

amounts of information from •Lab equipment and experiments•Computer Analysis•Human Analysis•Make visible to the world’s scientists

Without Bioinformatics, Human Genome Project could not have been achieved !!!

Goals of Bioinformatics Development and implementation of tools that enable efficient access to, and use and management of, various types of information.

Development of new algorithms and statistics with which to assess relationships among members of large data sets, such as methods to

- locate a gene within a sequence,- predict protein structure and/or function,- uncover the wealth of biological information

hidden in the mass of data- obtain a clear insight into the fundamental biological process of organisms.- identify malfunctions in these processes which lead to diseases- find approaches to improving drug discovery.

Bioinformatics Databases• Public databases are the most important

entity in bioinformatics• Store knowledge about

- Sequence e.g. EMBL- Structure e.g. PDB- Pathways e.g. KEGG- Interactions e.g. DIP- Diseases e.g. OMIMAnd many others …

• Can be searched in a variety of ways e.g. keyword, pattern, sequence

Cycle of Life

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Evolution

Sequence

Structure

Function

Ligand

Central Paradigm of Molecular Biology

Central Paradigm of Bioinformatics

Biochemical Function

Molecular Structure

Genetic Informatio

n

Symptoms

Real world of Bioinformatics1. Molecular medicine

More drug targetsPersonalized medicinePreventative medicineGene therapy

2. Microbial genome applicationsWaste cleanupClimate changeAlternative energy sourcesBiotechnologyAntibiotic resistanceForensic analysis of microbesThe reality of bio-weapon creationEvolutionary study

3. AgricultureCropsInsect resistanceImprove nutritional qualityGrow crops in poorer soils and that are drought resistant

4. Animals

5. Comparative studies

Bioinformatics Challenges

Biological Redundancy and multiplicity

Different sequences with similar structures

Difference structures with similar sequences

Organisms with similar genes

Multiple functions of single gene

Grouping of genes in pathways

Significance of relationships and similarities

Lack of Data

Referenceshttp://www.ncbi.nlm.nih.gov/About/primer/bioinformatics.html What is bioinformatics? An introduction and overview, N.M.

Luscombe, D. Greenbaum, M. Gerstein. Department of Molecular Biophysics and Biochemistry Yale University, New Haven, USA

Introduction to BioinformaticsIntroduction Bioinformatics, Stephen Taylor

Intro to BioInformatics, Esti Yeger-Lotem, Doron Lipson, Lecture I: Introduction & Text Based Search

Emerging Areas in BIOINFORMATICS, Dr. Gulshan Wadhwa, National Seminar on "Intellectual Property Rights in Bioinformatics and Biotechnology” September 15 2005 Bioinformatics Centre, Pondicherry University

BIOINFORMATICS Introduction, Mark Gerstein , Yale University bioinfo.mbb.yale.edu/mbb452a

http://www.cs.usfca.edu/~pfrancislyon/resources/cs686_01_intro.pdf

…………….. Some downloaded ppt.

Some Web Related to Bioinformatics

http://bio-bio-1.wikispaces.comhttp://www.dnalc.org/http://www.bioinformaticsatschool.eu/