Bio-bio-1 Team Advisor: Dr. Supten Sarbadhikari Members: Fokhruz Zaman Zohirul Alam Tiemoon Saddam Hossain Farjana 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 + Informatics BioBios (Greek)Life InformaticsInformatique (French) Data Processing

Why Use of Bioinformatics Why bioinformatics To Find an answer quickly - in-silicobiology is faster than in-vitro Massive 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 TypeData SizeTopics Raw DNA sequence8.2 million sequences (9.5 billion bases) Separating coding and non-coding regions Identification of introns and exons Gene product prediction Forensic analysis Protein sequence300,000 sequences (~300 amino acids each) Sequence comparison algorithms Multiple sequence alignments algorithms Identification of conserved sequence motifs Macromolecular structure 13,000 structures (~1,000 atomic coordinates each) Secondary, tertiary structure prediction 3D structural alignment algorithms Protein geometry measurements Surface and volume shape calculations Intermolecular interactions

Data TypeData SizeTopics Genomes40 complete genomes (1.6 million – 3 billion bases each) Characterisation of repeats Structural assignments to genes Phylogenetic analysis Genomic-scale censuses (characterisation of protein content, metabolic pathways) Linkage analysis relating specific genes to diseases Gene expressionlargest: ~20 time point measurements for ~6,000 genes Correlating expression patterns Mapping expression data to sequence, structural and biochemical data Quantity of each type of data that is currently (August 2000) available

Why Use of Bioinformatics  Biological 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 !!!

 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. OMIM And many others … Can be searched in a variety of ways e.g. keyword, pattern, sequence

Cycle of Life KKAVINGEQIRSISDLHQTLKK WELALPEYYGENLDALWDCLTG VEYPLVLEWRQFEQSKQLTENG AESVLQVFREAKAEGCDITIE Evolution Sequence Structure Function Ligand

Central Paradigm of Molecular Biology

Central Paradigm of Bioinformatics Biochemical Function Molecular Structure Genetic Information Symptoms

1. Molecular medicine More drug targets Personalized medicine Preventative medicine Gene therapy 2. Microbial genome applications Waste cleanup Climate change Alternative energy sources Biotechnology Antibiotic resistance Forensic analysis of microbes The reality of bio-weapon creation Evolutionary study

3. Agriculture Crops Insect resistance Improve nutritional quality Grow 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

References 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 Bioinformatics Centre, Pondicherry University BIOINFORMATICS Introduction, Mark Gerstein, Yale University bioinfo.mbb.yale.edu/mbb452a …………….. Some downloaded ppt.

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