|
|
Biology
| Optimization Models in Computational Biology |
|
| Description: |
This course will introduce a series of optimization models that find applications to various problems in bioinformatics and computational biology. The basics of the following topics will be covered: dynamic programming; graph algorithms (paths and flows); clustering and trees; linear, non-linear, and integer programming (including convex polytopes); certain probabilistic models; and very limited algebraic statistics. The applications of these optimization models to bioinformatics and computational biology will be illustrated by studying problems such as sequence motif search, DNA sequence alignment (including parametric sequence alignment), recombinations and other related phylogenetic problems, protein sequencing, and protein structure prediction (including side-chain positioning, scoring functions for threading, molecular dynamics etc.).
Course material created by Professor Bala Krishnamoorthy. |
| Target audience: |
Graduate |
| Institution: |
Washington State University |
| Materials available: |
Problem sets or projects, Course outline or syllabus, Textbook recommendations |
| Products: |
MATLAB |
Submitted: Jul 30, 2008
|
| Introduction to Computational Biology and Chemistry |
|
| Description: |
This course explores models that arise in biology and chemistry and how they're analyzed using modern mathematical and computational techniques. Topics covered are statistical models, discrete- and continuous- time dynamical models, and stochastic models. Applications will sample a wide range of scales, from biomolecules to population dynamics, with an emphasis on common mathematical concepts and computational techniques. Throughout, themes will include interpretation of existing data and predictions for new experiments.
Course material created by Professor Eric Shea-Brown. |
| Target audience: |
Advanced undergraduate (3rd or 4th year) |
| Institution: |
University of Washington |
| Materials available: |
Problem sets or projects, Course outline or syllabus, Textbook recommendations, Downloadable code or data files |
| Products: |
MATLAB |
Submitted: Jul 30, 2008
|
| Systems Biology |
|
| Description: |
This course introduces the mathematical modeling techniques needed to address key questions in modern biology. An overview of modeling techniques in molecular biology and genetics, cell biology and developmental biology is covered. Key experiments that validate mathematical models are also discussed, as well as molecular, cellular, and developmental systems biology, bacterial chemotaxis, genetic oscillators, control theory and genetic networks, and gradient sensing systems. Additional specific topics include: constructing and modeling of genetic networks, lambda phage as a genetic switch, synthetic genetic switches, circadian rhythms, reaction diffusion equations, local activation and global inhibition models, center finding networks, general pattern formation models, modeling cell-cell communication, quorum sensing, and finally, models for Drosophila development.
Course material created by Professor Alexander van Oudenaarden. |
| Target audience: |
Graduate |
| Institution: |
Massachusetts Institute of Technology |
| Materials available: |
Problem sets or projects, Course outline or syllabus, Textbook recommendations, Downloadable code or data files |
| Products: |
MATLAB |
Submitted: Jul 22, 2008
|
| Biosciences Books |
|
|
A catalog listing of titles from The MathWorks books program. The texts present theory, real-world examples, and exercises using MATLAB, Simulink, and other MathWorks products.
Submitted: Mar 12, 2008
|
|
|
