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20.482J / 6.581J Foundations of Algorithms and Computational Techniques in Systems Biology

Spring 2006

Predicted 3-D structure of the Rad checkpoint complex.The role of the Rad checkpoint complex was inferred from the 3-D structure predicted by comparative modeling at Lawrence Livermore National Laboratory. The Rad complex delays cell division to allow time for DNA repair to take place. (Image courtesy of the U.S. Department of Energy Genomics: GTL Program.)

Course Highlights

This course features a complete set of lecture notes and assignments.

Course Description

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.

Technical Requirements

Special software is required to use some of the files in this course: .zip, .dat, .m, .qif, and .bmp.





Syllabus

Amazon logo Help support MIT OpenCourseWare by shopping at Amazon.com! MIT OpenCourseWare offers direct links to Amazon.com to purchase the books cited in this course. Click on the Amazon logo to the left of any citation and purchase the book from Amazon.com, and MIT OpenCourseWare will receive up to 10% of all purchases you make. Your support will enable MIT to continue offering open access to MIT courses.


Recommended Textbooks

Amazon logo Schlick, T. Molecular Modeling and Simulation: An Interdisciplinary Guide. New York, NY: Springer, 2002. ISBN: 9780387954042.

Amazon logo Allen, M. P., and D. J. Tildesley. Computer Simulation of Liquids. New York, NY: Oxford University Press, 1989. ISBN: 9780198556459.

Amazon logo Trefethen, L. N., and D. Bau, III. Numerical Linear Algebra. Philadelphia, PA: SIAM, 1997. ISBN: 9780898713619.

Amazon logo Branden, C.-I., and J. Tooze. Introduction to Protein Structure. 2nd ed. New York, NY: Routledge, 1999. ISBN: 9780815323051.

Amazon logo Bertero, M., and P. Boccacci. Introduction to Inverse Problems in Imaging. New York, NY: Taylor & Francis, 1998. ISBN: 9780750304399.



Grading


ACTIVITIESPERCENTAGES
Homework80%
Class Participation20%





Calendar


LEC #TOPICSKEY DATES
Protein Modeling
1Introduction and Protein Modeling Questions
2Models of Proteins
3Discrete Conformational Search
4Binding and Docking
5Molecular Dynamics SimulationHomework 1 due
6Molecular Dynamics and Electrostatics
7Continuum Electrostatic Modeling I
8Continuum Electrostatic Modeling II
9Electrostatic Optimization and DesignHomework 2 due
10Electrostatics Modeling
11Statistical Mechanics
Network Modeling
12Statistical Mechanics (cont.)
13Formulating and Simulating Network Models in BiologyHomework 3 due
14Formulating Models
15Nonlinear Dynamics and StabilityHomework 4 due
16Steady-State Problems
17Parameter Fitting and Estimation
18Parameter Estimation; Robustness, Fragility, ControlHomework 5 due
Image Modeling
192-D and 3-D Light Microscopy; Image Reconstruction
20Deconvolution
21Deconvolution II
22Blind DeconvolutionHomework 6 due
23Optical Flow
24High-Throughput Data and its Analysis
25Inference and Statistics
26RoundupHomework 7 due




Lecture Notes

This section contains documents created from scanned original files, which are inaccessible to screen reader software. A "#" symbol is used to denote such documents.

Notes from lectures 3 through 25 are courtesy of Laura Proctor. Used with permission.


LEC #TOPICS
Protein Modeling
1Introduction and Protein Modeling Questions (PDF)
2Models of Proteins (PDF)
3Discrete Conformational Search (PDF)#
4Binding and Docking (PDF)#
5Molecular Dynamics Simulation (PDF)#
6Molecular Dynamics and Electrostatics (PDF)#
7Continuum Electrostatic Modeling I (PDF)#
8Continuum Electrostatic Modeling II (PDF)#
9Electrostatic Optimization and Design (PDF)#
10Electrostatics Modeling (PDF 1)# (PDF 2)#
11Statistical Mechanics (PDF)#
Network Modeling
12Statistical Mechanics (cont.) (PDF)#
13Formulating and Simulating Network Models in Biology (PDF)#
14Formulating Models (PDF)#
15Nonlinear Dynamics and Stability (PDF)#
16Steady-State Problems (PDF)#
17Parameter Fitting and Estimation (PDF)#
18Parameter Estimation; Robustness, Fragility, Control (PDF)#
Image Modeling
192-D and 3-D Light Microscopy; Image Reconstruction (PDF)#
20Deconvolution (PDF)#
21Deconvolution II (PDF)#
22Blind Deconvolution (PDF)#
23Optical Flow (PDF)#
24High-Throughput Data and its Analysis (PDF)#
25Inference and Statistics (PDF)#
26Roundup





Supplemental Notes

Adjoint Sensitivity Analysis for Optimization (PDF) (Courtesy of Joshua Apgar and Jared Toettcher. Used with permission.)





Assignments

Special software is required to use some of the files in this section: .zip, .dat, .m, .qif, and .bmp.


ASSIGNMENTSAUXILIARY FILES
Problem Set 1 (PDF)pair-dat.zip (ZIP - 2.1 MB) (The ZIP file contains: pair.dat.)
pair-small.dat (DAT - 7.8 MB)
pair-tiny.dat (DAT - 1.7 MB)
Problem Set 2 (PDF)estatic.m (M)
moldyn.m (M)
reflect.m (M)
Problem Set 3 (PDF)calcp.m (M)
computeReactionPotential.m (M)
estatic_svd.m (M)
gencolloc.m (M)
readpanel.m (M)
readpanels.m (M)
loadComplex.m (M)
sphere48.qif (QIF)
sphere192.qif (QIF)
sphere768.qif (QIF)
Problem Set 4 (PDF)integrate.m (M)
lambda.m (M)
newton.m (M)
Problem Set 5 (PDF)descent.m (M)
lambda2.m (M)
Problem Set 6 (PDF)mandrill.bmp (BMP)
circul.m (M)
load_data.m (M)
loadWaveletBasis.m (M)
partial_inv.m (M)



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