03-310/42-334. Introduction to Computational Biology, Spring 2006 (9 units)

This course presents an overview of important applications of computers to solve problems in biology. It is intended for students without computer programming experience (students with a desire to apply programming methods to these problems should take 03-510/42-534 or 03-710/42-734). Major topics covered are computational molecular biology (analysis of protein and nucleic acid sequences), biological modeling and simulation (including computer models of population dynamics, biochemical kinetics, cell pathways, neuron behavior, and mutation) and biological imaging (digital image processing, morphological image analysis, and image classification). Course work consists of homework assignments making use of software packages for these applications. Students may only use one of the following for credit, 03-310, 03-311, 03-510 or 03-710. Prerequisites: Modern Biology (03-121) and Calculus II (21-112/21-122) and Computing Skills Workshop (99-101) or equivalents.

Lectures for 03-510/42-534/03-710/42-734 (Computational Biology), 03-310/42-334 (Introduction to Computational Biology) and the mini-course 03-311 (Introduction to Computational Molecular Biology) will be given in common on Tuesdays and Thursdays from 3:00 to 4:20.

(1) There will be a recitation from 11:30 to 12:20 on Mondays in the Hunt Library Macintosh Cluster. The recitation session will include review of material covered during the previous week and answers to questions regarding homeworks.

(2) You are encouraged to send e-mail to the TA or Dr. Murphy to pose questions or to schedule a time to meet.

50% of the course grade will be derived from homework assignments. 20% will be derived from the midterm exam (March 7th) and 30% from the final exam. Homework must be submitted by the beginning of class on the due date in order to receive any credit. No credit will be given after that date unless an extension has been requested at least 24 hours PRIOR to the due date. Most homework assignments will include opportunities for extra credit, and there will be occasional, brief quizzes for extra credit.

Discussion and collaboration on homework problems between students is allowed, but each student must prepare his or her own assignment. Students may not copy any portion of a homework assignment from another student, nor may they jointly prepare all or part of an assignment. Examples of unacceptable collaboration are:

(1) jointly doing an analysis and then printing multiple copies of the results.

(2) using any portion of a spreadsheet or program written by someone other than the instructor.

(3) following a method suggested by a student without being able to explain the method.

Computational Molecular Biology: Analysis of Nucleic Acid and Protein Sequence (Jan. 17 through Mar. 2).The methods by which computers are used to manipulate and analyze sequences and structures will be covered. Students will become familiar with Internet-based information services relevant to biology (including Entrez and the BLAST server) and will gain understanding of the principles behind major sequence analysis methods. Topics will include:

-information retrieval with Entrez and Web browsers

-statistics of sequence patterns

-basics of machine learning for molecular biology

-pairwise sequence alignment

-comparison with sequence databases

-finding sequence motifs

-finding protein coding regions

-finding genes

-clustering genes by expression

-prediction of macromolecular properties

-retrieving and displaying macromolecular structures

Computational Cell Biology: Biological Modeling and Imaging (March 9 to May 4). A range of approaches used to model the behavior of biological systems will be covered. Underlying concepts covered include recursion relations, phase plane analysis, parameter identifiability, and description of systems using differential equations. Applications of digital image processing and analysis to biological images, especially from fluorescence microscopy, will be discussed, particularly in the context of building models from images. Spreadsheets (e.g., Excel), symbolic mathematics packages (e.g., Mathematica or Maple), and Matlab will be used. Specific topics include:

-recursion relations in population dynamics

-biochemical kinetics

-cellular pathways

-simulation of action potentials

-compartmental analysis

-acquiring and viewing digital images

-image processing: basic operations, automation

-pattern analysis: feature extraction, classification, clustering

-model building from images

D.W. Mount, Bioinformatics: Sequence and Genome Analysis (2nd edition), Cold Spring Harbor Laboratory Press, Cold Spring Harbor, New York, 2004

Warren J. Ewens, Gregory R. Grant, Statistical Methods in Bioinformatics: An Introduction, Springer -Verlag, 2001 (ISBN: 0387952292)

Pavel A. Pevzner, Computational Molecular Biology: An Algorithmic Approach, MIT Press, 2000 (ISBN: 0262161974)

Peter Clote, Rolf Backofen, Computational Molecular Biology: An Introduction, John Wiley & Sons, Ltd., 2000 (ISBN: 0471872520)

Richard Durbin, Sean R. Eddy, Anders Krogh, Graeme Mitchison, Biological Sequence Analysis: Probabilistic models of proteins and nucleic acids, Cambridge University Press, 1998 (ISBN: 0521629713)

Andreas D. Baxevanis, B.F. Francis Ouellette, Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, Wiley-Interscience, 1998 (ISBN: 0471383910).

Michael Gribskov, John Devereux, Sequence Analysis Primer, (UWBC Biotechnical Resource Series) original issue, Stockton Press, 1990 (ISBN: 156159007X); reissue, Oxford University Press, 1994 (ISBN: 0195098749)

Michael S. Waterman (ed.), Mathematical Methods for DNA Sequences, CRC Press, Inc., Boca Raton, Florida, 1989 (ASIN: 084936664X)

D. Fasman, Prediction of protein structure and the principles of protein conformation, Plenum Press, New York, 1989 (ISBN: 0306431319)

Lee A. Segel, Modeling dynamic phenomena in molecular and cellular biology, Cambridge University Press, Cambridge University Press, 1984 (ISBN: 052127477X)

John A. Jacquez, Compartmental Analysis in Biology and Medicine, Second Edition, The University of Michigan Press, Ann Arbor, 1985 (ASIN: 0472100637)

E.K. Yeargers, R.W. Shonkwiler, and J.V. Herod, An Introduction to the Mathematics of Biology (with Computer Algebra Models), Birkhauser, Boston, 1996