Spring Semester 2003 10.555 Bioinformatics: Principles, Methods and Applications Instructors Gregory Stephanopoulos 1 and Isidore Rigoutsos 2 9 units (H), Class meets Tuesdays 2-5 pm, Room 56-154 This course provides an introduction to Bioinformatics. We define this field as the principles and computational methods aiming at the upgrade of the information content of the large volume of biological data generated by genome sequencing, as well as cell- wide measurements of gene expression (DNA microarrays), protein profiles (proteomics), metabolites and metabolic fluxes. Additionally, bioinformatics is concerned with whole organism data, especially human physiological variable measurements including organ function assessments, hormone levels, blood flow, neuronal activity etc., that characterize normal and pathophysiology. The overall goal of this data upgrade process is to elucidate cell function and physiology from a comprehensive set of measurements as opposed to using single markers of cellular function. Fundamentals from systems theory will be presented to define modeling philosophies and simulation methodologies for the integration of genomic and physiological data in the analysis of complex biological processes, e.g. genetic regulatory networks and metabolic pathways. Various computational methods will address a broad spectrum of problems in functional genomics and cell physiology, including; analysis of sequences, (alignment, homology discovery, gene annotation), gene clustering, pattern recognition/discovery in large-scale expression data, elucidation of genetic regulatory circuits, analysis of metabolic networks and signal transduction pathways. Applications of bioinformatics to metabolic engineering, drug design, and biotechnology will be also discussed. COURSE OUTLINE Part I: INTRODUCTION, DEFINITIONS, PRIMERS Lecture 1: February 4 - Historical perspectives, definitions - Impact of genomics on problems in molecular and cellular biology; need for integration and quantification, contributions of engineering - Overview of problems to be reviewed in class: Sequence driven and data driven problems - Overview of course methods - Integrating cell-wide data at the cellular level - Connection with broader issues of physiology 1 Department of Chemical Engineering, Room 56-469, gregstep@mit.edu , 253-4583 2 Manager, Bioinformatics & Pattern Discovery, Computational Biology Center, IBM Thomas J Watson Research Center, rigoutso@us.ibm.com