Learning and Modeling Biological Networks

CS 838 (Spring 2003): Learning and Modeling Biological Networks

General Course Information

Instructors:
- Mark Craven
  craven AT biostat DOT wisc DOT edu
  Office: 6730 Medical Sciences Center (corner of Charter and University)
- David Page
  page@biostat.wisc.edu
  Office: 6743 Medical Sciences Center (corner of Charter and University)
- Jude Shavlik
  shavlik@cs.wisc.edu
  Office: 6357 Computer Sciences
Prerequisite: CS/BMI 576 or CS 731 or CS 760 or consent of instructors
Meeting Time and Location: 2:30-3:45 MONDAY and FRIDAY, Engineering 3534 (note the new room)
Class Email Archive (send mail to list)

Course Overview and Requirements

This will be a special topics course that focusing on recent work that involves modeling metabolic, signaling, and gene regulation networks in cells, with a particular focus on using machine learning methods to induce models from data.

There are three parts to this course's requirements:

Students will be expected to present 2-3 papers.
Students will be expected to read each week's papers and participate in the discussions.
Students will do substantial class projects of their choice. Project proposals will be due early in the semester, and a progress report will be due mid-semester. Team projects are acceptable.

Students who are auditing the course will be expected to present one paper and attend regularly.

Possible Readings

Background Reading

L. Hunter. Molecular Biology for Computer Scientists. In Artificial Intelligence and Molecular Biology, L. Hunter editor, 1993, AAAI Press.
Mark Craven's 576 Lecture Notes on Introduction to Molecular Biology
DOE Primer on Molecular Genetics
R. Brent. Genomic Biology. Cell 100:169-183, 2000.
D. Endy and R. Brent. Modelling Cellular Behavior. Nature 409:391-395, 2001.
H. McAdams and A. Arkin. Simulation of Prokaryotic Genetic Circuits. Annual Review of Biophysics and Biomolecular Structure 27:199-224, 1998.
C. Rao and A. Arkin. Control Motifs for Intracellular Regulatory Networks. Annual Review of Biomedical Engineering 3:391-419, 2001.
Computational Modeling of Genetic and Biochemical Networks, MIT Press

Learning and Modeling Genetic Networks

D. Pe'er, A. Regev and A. Tanay. Minreg: Inferring an Active Regulator Set. Bioinformatics 18(Supplement 1):S258-S267, 2002.
A. Hartemink, D. Gifford, T. Jaakkola and R. Young. Using Graphical Models and Genomic Expression Data to Statistically Validate Models of Genetic Regulatory Networks. In Proceedings of the Sixth Pacific Symposium on Biocomputing, 2001.
A. Hartemink, D. Gifford, T. Jaakkola and R. Young. Combining Location and Expression Data for Principled Discovery of Genetic Regulatory Network Models. In Proceedings of the Seventh Pacific Symposium on Biocomputing, 2002.
L. Chrisman, P. Langley, S. Bay and A. Pohorille. Incorporating Biological Knowledge into Evaluation of Causal Regulatory Hypotheses. In Proceedings of the Eighth Pacific Symposium on Biocomputing, 2003.
S. Bay, J. Shrager, A. Pohorille and P. Langley. Revising Regulatory Networks: From Expression Data to Linear Causal Models. Submitted, 2002.
D. Pe'er, A. Regev, G. Elidan and N. Friedman. Inferring Subnetworks from Perturbed Expression Profiles. In Proceedings of the Ninth International Conference on Intelligent Systems for Molecular Biology, 2001.
E. Segal, Y. Barash, I. Simon, N. Friedman and D. Koller. From Promoter Sequence to Expression: A Probabilistic Framework. In Proceedings of the Sixth Annual International Conference on Computational Molecular Biology (RECOMB), 2002.
T. Ideker, V. Thorsson and R. Karp. Discovery of Regulatory Interactions through Perturbation: Inference and Experimental Design. In Proceedings of the Fifth Pacific Symposium on Biocomputing, 2000.
A. Tanay and R. Shamir. Computational Expansion of Genetic Networks Proceedings of the 9th International Conference on Intelligent Systems for Molecular Biology, 2001.
C. Yoo, V. Thorsson and G. Cooper. Discovery of Causal Relationships in a Gene Regulation Pathway from a Mixture of Experimental and Observational DNA Microarray Data In Proceedings of the Seventh Pacific Symposium on Biocomputing, 2002.
D. Sharp and J. Reinitz Prediction of Mutant Expression Patterns using Gene Circuits. BioSystems 47:79-90, 1998.

Learning and Modeling Metabolic Networks

N. Angelopoulos and S. Muggleton. Machine Learning Metabolic Pathway Descriptions using a Probabilistic Relational Representation. Electronic Articles in Computer and Information Science, 2002.
C. Bryant, S. Muggleton, S. Oliver, D. Kell, P. Reiser and R. King. Combining inductive logic programming, active learning, and robotics to discover the function of genes. Electronic Transactions in Artificial Intelligence, 2001.
P. Reiser, R. King, D. Kell, S. Muggleton, C. Bryant, and S. Oliver. Developing a logical model of yeast metabolism. Electronic Transactions in Artificial Intelligence, 2001.
T. Ideker, V. Thorsson, J. Ranish, R. Christmas, J. Buhler, J. Eng, R. Bumgarner, D. Goodlett, R. Aebersold, and L. Hood. Integrated Genomic and Proteomic Analyses of a Systematically Perturbed Metabolic Network. Science, 292: 929-934, 2001.
C. Schilling, S. Schuster, B. Palsson and R. Heinrich. Metabolic Pathway Analysis: Basic Concepts and Scientific Applications in the Post-genomic Era. Biotechnology Progress, 15:296-303, 1999.
C. Schilling, J. Edwards, D. Letscher and B. Palsson. Combining Pathway Analysis with Flux Balance Analysis for the Copmprehensive Study of Metabolic Systems. Biotechnology and Bioengineering, 71(4):286-306, 2000.
M. Covert and B. Palsson. Transcriptional Regulation in Constraints-based Metabolic Models of Escherichia coli. Journal of Biological Chemistry, 277(31):28058-28064, 2002.
J. Papin, N. Price and B. Palsson. Extreme Pathway Lengths and Reaction Participation in Genome-Scale Metabolic Networks. Genome Research, 12:1889-1900, 2002.
M. Antoniotti, F. Park, A. Policriti, N. Ugel and B. Mishra. Foundations of a Query and Simulation System for the Modeling of Biochemical and Biological Processes. In Proceedings of the Eighth Pacific Symposium on Biocomputing, 2003.

Learning and Modeling Signaling Networks

A. Asthagiri and D. Lauffenburger. Bioengineering Models of Cell Signaling. Annual Review of Biomedical Engineering, 2:31-53, 2000.
S.Shvartsman, C. Muratov and D. Lauffenburger. Modeling and Computational Analysis of EGF Receptor-Mediated Cell Communication in Drosophila Oogenesis. Development, 129(11):2577-2589, 2002.
H. Wiley, S. Shvartsman and D. Lauffenburger. Computational Modeling of the EGF Receptor System: A Paradigm for Systems Biology. Trends in Cell Biology, 13(1):43-50, 2003.
B. Shapiro, A. Levchenko and E. Mjolsness. Automatic Model Generation for Signal Transduction with Applications to MAP-Kinase Pathways.

Schedule of Presentations

date	required readings	recommended readings	presenter
1/24	Genomic Biology Modelling Cellular Behavior	Molecular Biology for Computer Scientists	--
1/27	From Promoter Sequence to Expression: A Probabilistic Framework	--	Joe Bockhorst
1/31	Minreg: Inferring an Active Regulator Set.	--	Irene Ong
2/5 (Wednesday)	continue From Promoter Sequence to Expression: A Probabilistic Framework	--	Joe Bockhorst
2/7	Combining Inductive Logic Programming, Active Learning, and Robotics to Discover the Function of Genes	Developing a logical model of yeast metabolism.	Mark Rich
2/10	Integrated Genomic and Proteomic Analyses of a Systematically Perturbed Metabolic Network	--	Elenita Ilieva Kanin
2/14	Revising Regulatory Networks: From Expression Data to Linear Causal Models	--	Wei Luo
2/17	Discovery of Regulatory Interactions through Perturbation: Inference and Experimental Design	--	Cheryl Barkauskas
2/21	Transcriptional Regulation in Constraints-based Metabolic Models of Escherichia coli	--	Yue Pan
2/24	topic: High-throughput Methods for Gathering Data about Cells (no readings)	--	Chris Warren
2/28	NO CLASS	--	--
3/3	Prediction of Mutant Expression Patterns using Gene Circuits	--	Aaron Darling
3/7	Computational Expansion of Genetic Networks	--	Burr Settles
3/10	NO CLASS -- Uri Keich talk at 2:25pm in B135 Van Vleck	--	--
3/14	Computational Modeling of the EGF Receptor System: A Paradigm for Systems Biology	--	Michael Molla
3/17	NO CLASS -- SPRING BREAK	--	--
3/21	NO CLASS -- SPRING BREAK	--	--
3/24	project discussion	--	--
3/28	Discovery of Causal Relationships in a Gene Regulation Pathway from a Mixture of Experimental and Observational DNA Microarray Data	--	Keith Noto
3/31	tutorial on enzyme kinetics	Energy and Enzymes Michaelis-Menten Kinetics Michaelis-Menten Kinetics Applet Symbolism and Terminology in Enzyme Kinetics	Dan McFarlin
4/4	Automatic Model Generation for Signal Transduction with Applications to MAP-Kinase Pathways	--	Beverly Seavey
4/7	Inferring Subnetworks from Perturbed Expression Profiles	--	Cheryl Barkauskas
4/11	Foundations of a Query and Simulation System for the Modeling of Biochemical and Biological Processes	--	Aaron Darling
4/14	Extreme Pathway Lengths and Reaction Participation in Genome-Scale Metabolic Networks	--	Yue Pan
4/18	NO CLASS	--	--
4/21	Using Graphical Models and Genomic Expression Data to Statistically Validate Models of Genetic Regulatory Networks	--	Wei Luo
4/25	--	--	--
4/28	Effects of Escherichia coli Physiology on Growth of Phage T7 In Vivo and In Siloco	--	guest lecturer: Prof. John Yin
5/2	PROJECT PROGRESS REPORTS	--	--
5/5	--	--	--
5/9	--	--	--

Research Groups and other Relevant Links

Mark Craven

Last modified: Mon Apr 14 09:06:57 CDT 2003