Problems and Perspectives in Computational Molecular Biology

Cornell University
Fall 2001

The next presentation

Monday December 10
Mike Stillman and Harry Tsai (Math)

(1) Using graphical models and genomic expression data to statistically validate models of genetic regulatory networks. abstract (2) Supervised harvesting of expression trees. abstract

Future presentations

Previous presentations (+ presentation files)

New Submit your Critiques online or download a Paper Critiques form

Time and Place

Mondays 1:25 pm to 2:15 pm
Comstock Hall B108

1 credit, S/U only.
Prerequisites:  Permission of instructor.
The seminar is required from students of the Computational Molecular Biology Program.


Golan Yona (CS), Susan McCouch (PB), Marty Wells (BSCB)
This course is cross-listed as CS 726 (Computer Science),  PB 726 (Plant Breeding) and BSCB 726 (Biometrics)



This is a weekly seminar series discussing timely topics of computational molecular biology.  The course addresses methodological approaches to sequence annotation, protein structure and function relationships, evolutionary relationships across species.  Statistical and deterministic computational approaches will be covered and specific and detailed biological examples will be discussed.

Topics of interest will be discussed in relation to papers prepared by teams of students and/or faculty.  We will pair students from biology backgrounds with students from math, computer science and statistics for paper preparation.  Students will summarize the salient questions addressed by the paper, the research methods used and the results obtained.  At the end of the presentation, questions should be listed on an overhead slide to initiate discussion in the group. Topics covered during the Fall 2001 semester:

Suggested Papers

Sequence analysis

Pairwise comparison/database search

Multiple alignments, Profiles

Hidden markov models

Alternative representations, sequence-function relationships

Structure analysis

Structure comparison (Dali, CE, Structal, Geometric hashing)

Automatic detection of domains

Fold recognition, Threading, Structure prediction

Structural/evolutionary profiles

Gene expression


Introduction to Microarray Technology


Imaging and normalization



Singular value decomposition, pca's, classification

Large-scale analysis

Co-evolution, Protein-protein interaction


  1. Waterman, M. S. (1995). Introduction to computational biology. Chapman & Hall, London.
  2. Setubal, J. C. & Meidanis, J. (1996). Introduction to computational molecular biology. PWS Publishing Co., Boston.
  3. Methods in Enzymology, vol 266 (1996). Edited by R. F. Doolittle.
  4. Durbin, Eddy, Krogh, Mitchison (1998). Biological sequence analysis.
  5. Baldi, P. & Brunak, S. (1998). Bioinformatics: the machine learning approach.
  6. Bioinformatics: Sequence, structure, and databanks. Edited by D. Higgins and W. Taylor. Oxford University Press.


Nature Structural Biology
Proceedings of the National Academy of Sciences
Protein Science
Proteins: Structure, Function, and Genetics
Protein Engineering
Nucleic Acids Research
Journal of Computational Biology
Trends in Biochemical Sciences
Molecular Microbiology

Web journals

Science's Next Wave
BioMedNet 'webzine'

Paper Search and Misc.

Biochemistry and Molecular Biology Journals
IDEAL homepage
PubMed (Medline)
NEC archive
e-Print archive
citation reports (impact factor of scientific journals)

Background reading

For a survey of the classic algorithms for sequence comparison and the statistics of sequence alignment you can download one of the following documents Recommended books and book chapters on