Instructors:
Teaching fellows and problem set consultants:
Daniel Janse Daniel_Janse@student.hms.harvard.edu
Abby McGuire
Jeremy Edwards
Harvard Computational Biology Studies
Program in Biological and Biomedical Sciences (BBS)
Harvard-MIT Division of Health Sciences and Technology (HST)
Open to upper level undergraduates, and all graduate students.
Course description: This course will assess the relationships
between sequence, structure and function in complex biological networks
as well as progress in realistic modeling of quantitative, comprehensive
functional-genomics analyses. Exercises will include algorithmic,
statistical, database, and simulation approaches and practical applications
to biotechnology, drug discovery and genetic engineering. Future
opportunities and current limitations will be critically assessed.
Problem sets and a course project will emphasize hands-on analyses using
these concepts.
The prerequisite is enthusiastic interest in molecular biology, statistics, and computing.
Schedule and topics for Fall 1999:
Date Topics
Tue Sep 21 Given the building blocks of life & computers, then what? Thu Sep 23 Metrics, models, and molecular databases: How and Why? Tue Sep 28 High-level statistics, database, and programming tools Thu Sep 30 Genome sequencing: new methods and results Tue Oct 5 Comparative genomics: Gene-finding and pathways Thu Oct 7 3D homology modeling, molecular dynamics ... but function? Tue Oct 12 Hidden Markov Models: probabilistic protein interaction motifs Thu Oct 14 Regulatory networks: DNA chip/microarray analyses Tue Oct 19 Hierarchical clustering (e.g. using RNA levels) Thu Oct 21 Regulatory networks: DNA & RNA interaction motifs Tue Oct 26 Dynamic programming, blast Thu Oct 28 multiple sequence alignment algorithms Tue Nov 2 Mass spectrometric quantitation of proteins and metabolites Thu Nov 4 Metabolic network flux models: Differential equation & optimization methods Tue Nov 9 Signal transduction and cell interactions Tue Nov 16 What chemistry &biology can do for computing: self-assembly, genetic algorithms, neural nets Thu Nov 18 Information theory, simulated annealing and Monte Carlo Tue Nov 23 Darwinian organismal population growth Tue Nov 30 Association of polymorphisms with phenotypes Thu Dec 2 Drug Discovery and Design Tue Dec 7 Phylogenetics and evolution of function Thu Dec 9 Projects Tue Dec 14 Projects Thu Dec 16 Projects and course summary
Below are two texts for background reference (limited parts of these will be covered in this course). Recent articles will constitute the main readings.
Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic
Acids
by R. Durbin, S. Eddy, A. Krogh, and G. Mitchison. Cambridge University
Press, 1998.
Understanding the Control of Metabolism
by David Fell Frontiers in Metabolism Ser. ; No. 2, 1997