BGT 207: Computational Structural Biology

Mon/Wed 2:50-4:05pm Location: TBA

Prof:	Scott Schmidler
Email:	schmidler@stat.duke.edu
Office:	223D Old Chem Bldg
Phone:	684-8064
Office hours:	TBA

Course description:

This course provides a rigorous introduction to theory and computation for studying macromolecular structure and function. Topics include:

Basic structure of DNA, RNA, and proteins
Computer representation of molecules
Visualization, structure comparison, and database search
Molecular dynamics and Monte Carlo simulation
Statistical mechanical theory of protein folding
Protein and RNA structure prediction, threading, homology modeling
Protein function prediction and structure-based drug design
Protein-protein interactions
Machine learning and statistical classifiers, clustering, shape analysis
Recent topics in proteomics

This course is targeted towards students wishing to do methodological research in bioinformatics and computational biology. Engineers, computer scientists, mathematicians and statisticians will be exposed to a variety of quantitative problems arising from the modeling of macromolecular systems. Biological scientists will learn the mathematical principles underlying standard software tools in the field. A broad array of algorithms, simulation methods, statistical models, and pattern recognition tools will be discussed as applied to structural bioinformatics. The class will have a substantial programming component involving implementation of numerical algorithms. Throughout, emphasis is placed on developing formal models for representing biological knowledge and combining with statistical and experimental data.

Prerequisites: Basic probability or statistical mechanics; linear algebra; ability to program in a high-level language. Recommended: BGT 200 or Stat 104 or 213; BGT 203 or 204.

Enrolling in BGT 207: This course is cross-listed under BGT 207 and Stat 277. However this is a bioinformatics course, not a statistics course. ACES may require a permission number, which you may obtain by sending email to schmidler@stat.duke.edu. Please specify whether you wish to enroll under BGT 207 or Stat 277. All auditors will be required to enroll to audit with the Duke registrar.

This course is offered in alternate years.

Notices:

Please fill out the student information sheet and return to me during the first meeting.