Computational Molecular Biology (Spring’03)

1. Computational Molecular Biology (Spring’03) Chitta Baral Professor of Computer Science & Engg. http://www.public.asu.edu/~cbaral

2. Introduction • Biology • The science of life; that branch of knowledge which treats of living matter as distinct from matter which is not living; the study of living tissue. It has to do with the origin, structure, development, function, and distribution of animals and plants. • Molecular • Pertaining to, connected with, produced by, or consisting of, molecules • Molecule: the simplest structural unit of an element or compound • Computational • of or involving computation or computers • Computational Molecular Biology: Application of computation and computers in the study of biology (the science of life) at the molecular level.

3. Molecular Biology: issues of interest • Studying the interaction of molecules in an organism. • Some important molecules in an organism: • Sugar, carbohydrates • Proteins (made up of aminoacids) • E.g. Enzymes • Fats (lipids) • Oxygen (O2) • Acids (Deoxyribo Nucleic Acids) • Alcohols

4. CMB and health, diseases and disorders • The source of diseases and disorders can often be traced to activities inside cells. • The activities inside cells are often regulated by proteins (enzymes, ligands on cell surfaces, etc.) • Central Dogma: DNA  RNA  Proteins • The presence, absence and concentration of particular proteins inside cells are related to the expression of the genes that play a role in producing those proteins or in producing related proteins which help in transforming to/from these proteins. • Need to know which genes play a role in production of which proteins. • Need to know which genes are located where, and what is the DNA sequence of that gene. • How do we figure out what (various interacting chain of reactions/events -- pathways) is happening inside a cell? • If we suspect or guess of a particular reaction, or a set of reactions we can set up experiments to verify if indeed that is happening. But how do we guess? • Do micro-array experiments to study the gene expression (i.e., which genes are active). • By looking at the database of the same gene or similar (homologous) genes we can try to find out what is known about those genes in terms of their function (what proteins they produce) • From the information obtained and from knowledge about biochemistry we can make some guesses about particular reactions. • From guesses about particular reactions we try to guess about particular pathways.

5. CMB: some active research issues • Finding Genomes (gene sequencing) • Human genome (substantially completed) • 3 billion base pairs in 46 chromosomes. • Computing techniques are very important here. • Matching DNA sequences (algorithms) • Genes to phenotypes (Linkage analysis) • Relate genes to phenotypes (externally observable traits) by analyzing genomes of a family or over a population • Gene expression to pathways (dynamics of a cell) • Analyzing micro-array data (data mining, clustering) • Knowledge gathering, automatic annotation (from the literature) • Data and Knowledge integration across databases • Pathways prediction and analysis (reasoning about actions and events) • Drug design (AI planning) to modify the dynamics of the cell. • Phylogeny • Relating genes within and across species to understand their evolutionary relationship. • Prediction of secondary structure of proteins from their primary structure