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Biomolecular Kinetics and Cellular Dynamics (BE.420J)
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CC BY-NC-SA
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This subject deals primarily with kinetic and equilibrium mathematical models of biomolecular interactions, as well as the application of these quantitative analyses to biological problems across a wide range of levels of organization, from individual molecular interactions to populations of cells.

Subject:
Applied Science
Biology
Engineering
Life Science
Material Type:
Full Course
Provider Set:
MIT OpenCourseWare
Author:
Tidor, Bruce
Wittrup, Karl
Date Added:
09/01/2004
Design and Analysis of Algorithms
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CC BY-NC-SA
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Techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics include sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; greedy algorithms; amortized analysis; graph algorithms; and shortest paths. Advanced topics may include network flow, computational geometry, number-theoretic algorithms, polynomial and matrix calculations, caching, and parallel computing.

Subject:
Applied Science
Computer Science
Engineering
Material Type:
Full Course
Provider Set:
MIT OpenCourseWare
Author:
Moshkovitz, Dana
Tidor, Bruce
Date Added:
02/01/2012
Foundations of Algorithms and Computational Techniques in Systems Biology
Conditional Remix & Share Permitted
CC BY-NC-SA
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This subject describes and illustrates computational approaches to solving problems in systems biology. A series of case-studies will be explored that demonstrate how an effective match between the statement of a biological problem and the selection of an appropriate algorithm or computational technique can lead to fundamental advances. The subject will cover several discrete and numerical algorithms used in simulation, feature extraction, and optimization for molecular, network, and systems models in biology.

Subject:
Applied Science
Biology
Computer Science
Engineering
Life Science
Material Type:
Full Course
Provider Set:
MIT OpenCourseWare
Author:
Tidor, Bruce
White, Jacob
Date Added:
02/01/2006
Topics in Computational and Systems Biology
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CC BY-NC-SA
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This is a seminar based on research literature. Papers covered are selected to illustrate important problems and approaches in the field of computational and systems biology, and provide students a framework from which to evaluate new developments.
The MIT Initiative in Computational and Systems Biology (CSBi) is a campus-wide research and education program that links biology, engineering, and computer science in a multidisciplinary approach to the systematic analysis and modeling of complex biological phenomena. This course is one of a series of core subjects offered through the CSB Ph.D. program, for students with an interest in interdisciplinary training and research in the area of computational and systems biology.

Subject:
Applied Science
Biology
Engineering
Life Science
Material Type:
Full Course
Provider Set:
MIT OpenCourseWare
Author:
Burge, Christopher
Gilbert, Wendy
Gore, Jeff
Tidor, Bruce
White, Forest
Date Added:
09/01/2010