CS 600.439 Computational Biology Course Web Site, Fall 1995
Meeting time and place: Tuesdays and Thursdays, 4:30-5:45 p.m.,
Shaffer Hall Room 2
This course is co-listed in the Medical School, Department of
Biomedical Information Sciences, as ME 600.802.
Textbook: Introduction to Computational Biology: Maps, Sequences,
and Genomes by
Michael Waterman.
Publisher: Chapman & Hall.
Publication date: June 1995. 430 pages. ISBN 0-412-99391-0.
Homework assignments
Syllabus
Week 1, Sept. 12 and 14. Introduction, biological background.
Guest lecture on September 14 by Amy Voltz, Genome Data Base.
Topic: Molecular biology for non-biologists.
Reading:
Week 2, Sept. 19 and 21. Restriction maps and interval graphs.
Reading:
- Chapter 2 of Waterman.
- F. Alizadeh, R. Karp, D. Weisser, and G. Zweig (1995). Physical
mapping of chromosomes using
unique probes, J. Computational Biology 2:2, 159-184.
Week 3, Sept. 26 and 28.
Mapping clones and probes, continued. Sequence-tagged site mapping and
why it is computationally ``hard.'' Simulated annealing applied to
contig assembly.
Reading:
- Waterman, Sections 4.4.1 and 6.4. (The Alizadeh et al. article
is a more thorough treatment of the material in 6.4.)
- S. Kirkpatrick, C. Gelatt, and M. Vecchi. Optimization by
Simulated Annealing. Science 220:4598, May 13, 1983, 671-680.
Week 4, Oct. 3 and 5.
Mapping by fingerprinting. Sequencing by hybridization.
Reading:
Week 5, Oct. 10 and 12.
Sequence alignment, part 1: global distance alignment, global
similarity alignment, and local alignment.
Reading:
- Waterman, Chapter 9, Sections 9.3 through 9.8.
- Temple Smith and Mike Waterman (1981). Identification of
Common Molecular Subsequences. J. Mol. Biol. 147, 195-197.
Week 6, Oct. 17 and 19.
Special note: Thursday's class will be
held in the Genome Data Base classroom, at 2024 E. Monument St.,
Suite 1-200. Directions: take the shuttle bus down to the
medical school, which drops you on Monument Street at the intersection
with Wolfe St. Continue up Monument for 1.5 blocks. 2024 E. Monument
is a building on the left side of the street.
Sequence alignment, part 2: heuristic alignment methods including BLAST.
Genetic sequence and map databases.
Guest lecture on Oct. 19 by Kenneth Fasman.
Reading:
- S. Altschul, W. Gish, W. Miller, E. Myers, and D. Lipman (1990).
Basic Local Alignment Search Tool. J. Mol. Biology, 215, 403-410.
Alternatively, just read the
BLAST
Theory and Algorithm paper, available on-line.
- Waterman, Chapter 8.
- D.A. Benson, M. Boguski, D.J. Lipman, and J. Ostell (1994). GenBank.
Nucleic Acids Research 22(17): 3441-3444.
- Kenneth Fasman, A.J. Cuticchia, and David Kingsbury (1994). The GDB
Human Genome Data Base anno 1994. Nucleic Acids Research
22(17): 3462-3469.
- Kenneth Fasman, Stanley Letovsky, Robert Cottingham, and David Kingsbury
(1995). Improvements
to the GDB Human Genome Data Base. (This is a preprint of a 1995
Nucleic Acids Research article about GDB.
Week 7, Oct. 24 and 26.
Tuesday: inner product mapping for physical maps.
Thursday: ``Clinical Care and Biomedical Information: Cyberspace
Meets the Healthcare System'' (see below for details)
Special lecture, October 26: Edward Shortliffe, Professor of
Medicine and Computer Science, Stanford University will give The
Richard Polacsek Memorial Lecture. Thursday, October 26, 5:00pm.
Location: Hurd Hall, Johns Hopkins Hospital.
Directions: Hurd Hall is right in the midst of the hospital. If you
take the shuttle bus, you get off on Monument St. at the corner of
Wolfe St. Turn right on Wolfe and walk 1/2 block, and turn right
down the main driveway entering the hospital. Go in the main
entrance and Hurd Hall will be to your right.
Reading:
- Mark Perlin and A. Chakravarti (1993). Efficient construction of
high-resolution physical maps from yeast artificial chromosomes using
radiation hybrids: Inner Product Mapping. Genomics 18, 283-289.
Week 8, Oct. 31 and Nov. 2.
Algorithms for constructing amino acid substitution matrices.
Introduction to Hidden Markov Models.
Reading:
- D. Jones, W. Taylor, and J. Thornton (1992). The rapid generation
of mutation
data matrices from protein sequences. Computer Applications in the
Biosciences (CABIOS) 8:3, 275-282.
Week 9, Nov. 7 and 9.
Hidden Markov Models for multiple sequence alignment. HMMs will be
covered in detail first, followed by their application to the sequence
alignment problem. The structure of genes: exons, introns, and
inter-genic DNA.
Reading:
- Waterman, Chapter 10, especially section 10.5
- Anders Krogh, Michael Brown, I. Saira Mian, Kimmen Sjolander, and
David Haussler (1993). Hidden Markov Models
in Computational Biology: Applications to Protein Modeling (344K).
The figures are available in a separate file, which you get by
clicking here (1,009K).
This is technical report UCSC-CRL-93-32, UC
Santa Cruz, Dept. of Computer and Information Sciences. A shorter
version appeared in J. Mol. Biology, 1993.
Week 10, Nov. 14, 16, and 17.
Gene finding: search by content and search by signal.
Decision tree induction and its application to gene finding.
Special lecture on Friday, November 17, 10:30 a.m. in Shaffer
100:
Tomas Lozano-Perez, MIT Department of Computer Science will
speak to the Computer Science Department as part of the Distinguished
Lecture Series. The topic will be computational methods for drug
design, which includes protein folding and protein docking methods.
Reading:
- Jim Fickett and C.-S. Tung (1992),
Assessment of protein coding measures.
Nucleic Acids Research 20:24, 6441-6450.
Week 11, Nov. 21.
Decision trees and HMMs for gene finding. Protein and RNA
structure prediction.
Reading:
Week 12, Nov. 27, 28, and 30. Protein folding and threading.
Molecular evolutionary and evolutionary trees.
Special lecture on Monday, November 27: This week we will have
a special guest lecture by George Rose from the Dept. of Biophysics
and Biophysical Chemistry at the School of Medicine. Due to
scheduling constraints this lecture will be held on Monday, Nov. 27 at
4:00 p.m., in Mergenthaler Hall, Room 111. The title of the talk is
A Hierarchic Procedure for Predicting the Fold of a Protein from its
Amino Acid Sequence.
On November 30 we will have a guest lecture by Stan Letovsky from the
Genome Data Base, who will speak on constraint propagation for genomic
map construction.
Reading:
- Rajgopal Srinivasan and George Rose (1995). LINUS: A Hierarchic Procedure to
Predict the Fold of a Protein. PROTEINS: Structure, Function,
and Genetics 22, 81-99.
- Stanley Letovsky and Mary Berlyn (1992). CPROP: A Rule-Based Program
for Constructing Genetic Maps. Genomics 12, 435-446.
- Section 14.2.3 of Waterman.
- (optional) Arthur Delcher, Simon Kasif, Harry Goldberg, and
William Hsu (1993).
Protein Secondary Structure Modelling with Probabilistic Networks,
Proc. First Internatl. Conf. on Intelligent Systems for Molecular
Biology, 109-117.
-
Chapter 4 of the BioComputing Hypertext Coursebook by Andreas Dress.
(Optional, but you should definitely take a look at this!)
Week 13, Dec. 5 and 7.
Large-scale sequence assembly: how to sequence entire genomes.
The greedy algorithm for shotgun assembly. DNA computing.
Reading:
-
Science, July 28, 1995: all the articles on the
H. influenzae whole-genome sequence project.
- Leonard Adleman (1994).
Molecular Computation of Solutions to Combinatorial Problems.
Science, 266, November 11, 1994, 1021-1024.
- A Thousand Billion Billion Sums,
reprinted from The Economist, article about Adleman's experiment.
Week 14, Dec. 11.
Special lecture at 11:00 a.m. on
Monday, Dec. 11: Jim Fickett of Los Alamo National Laboratory will
be speaking at the Genome Data Base on "Understanding Tissue-Specific
Transcriptional Regulation: Contributions from Mathematics and
Biology. Directions to GDB are listed above in Week 6.
Assignments and grading
The grade will be based on problem sets, programming assignments, and
either a final exam or final project. There are a total of six assigments which count for a total of 70%
of the grade. The option of taking the exam or doing a project is up
to each student.
Useful resources for the course
Home Page for Computational Biology at Hopkins
Home Page for Computer Science at Hopkins