CBB 240/STA 270
Statistical Methods for Structural Bioinformatics,
Biophysics, and
Cheminformatics
Spring 2008
Tues/Thur 4:25-5:40
025 Old Chem Bldg
Course Description:
Introduction to methods of statistical inference and stochastic
modeling arising in computational biology, emphasizing techniques
relevant to applications in structural biology and biophysical
chemistry. Topics include:
- Discrete and continuous time stochastic processes
- Multivariate statistical modeling and classification
- Representation and analysis of spectral data
- Parameter estimation in statistical mechanical models
- Statistical computing, algorithms, and visualization
Applications will be drawn from a wide range of modeling and data
analysis challenges arising in structural bioinformatics, biophysics,
and cheminformatics. To include: modeling ion channels, evolutionary
rate models, stochastic chemical kinetics, theory and output analysis
for molecular simulations, random-walk p-values in Blast, biomarker
identification and classification of proteomics spectra, analysis of
AFM force spectroscopy curves, QSAR and 3D QSAR, statistical
potentials for protein structure prediction and molecular docking.
Course will involve homework assignments as well as
hands-on data analysis using statistical software. Students will
also complete a substantial project and are encouraged to select topics
related to their dissertation research or interests with instructor
guidance.
Prerequisites: Sta 213 or equivalent; Linear algebra. All
auditors require consent of instructor and will be required to enroll
as an auditor.