Representations and Algorithms for Molecular Biology
Fall 2000
- Classroom: To be announced.
- Time: To be announced.
- Professor:
Richard Lathrop
- Electronic Mail:
rickl@uci.edu
- Office: ICS 464E
- Office Hours: To be announced.
- Textbook: To be announced.
Course Goals and Description:
Computational methods in molecular biology, aimed at those interested
in learning about this interdisciplinary area. Course assumes no
background in biology; instead, studies the underlying analysis and
algorithms involved. Approaches the molecular level from a
mechanical, object-oriented perspective. Covers computational
approaches to understanding and predicting the structure, function,
interactions, and evolution of DNA, RNA, proteins, and related
molecules and processes. Topics include sequence similarity and
pattern matching; protein structure prediction; molecular force
fields, mechanics and dynamics; drug design and discovery; genome map
assembly and sequencing; forensic DNA; computing with DNA.
Other topics may be added based on student interest.
This course is intended to complement the existing ``hands-on''
computer based courses Biological Sciences 123/223 (``Computer
Applications in Molecular Biology'' / ``Computational Molecular
Biology''), which give a very practical introduction to using
computer tools in molecular biology. In contrast, this course
emphasizes the computational analysis and algorithms involved, and
spends very little time discussing how to run currently existing
molecular biology software tools.
Prerequisites:
A basic course in algorithms, or a basic course in molecular biology,
or consent of instructor.
Reading:
Required texts (may be changed in the Fall):
Introduction to Computational Molecular Biology
by Joao Setubal and Joao Meidanis.
Recommended texts (may be changed in the Fall):
Bioinformatics: The Machine Learning Approach
by Pierre F. Baldi.
Biochemistry: A Short Course
by Harry R. Matthews, Richard Freedland, and Roger L. Miesfeld.
Introduction to Protein Structure
by Carl Branden and John Tooze.
Molecular Modeling: Principles and Applications
by A.R. Leach.
Other background texts:
Introduction to Computational Biology: Maps, sequences and genomes
by Michael S. Waterman.
Artificial intelligence and molecular biology
edited by Lawrence Hunter.
Biological molecules
by C.A. Smith and E.J. Wood.
Biological Sequence Analysis
by R. Durbin, S. Eddy, A. Krogh, G. Mitchison.
Mathematical methods for DNA sequences
edited by Michael S. Waterman.
The majority of material for the class will be contained in the
lectures; there will also be regular assigned readings in the texts,
and xeroxed articles from the domain literature. Note that readings
do not substitute for the lectures.
Grading:
There will be a final project requiring both computational analysis
and molecular biology data, which will result in a brief (5-10 pages)
conference-style written report (25%); a conference-style talk
(25%); and a conference-style poster presentation (25%). Homework
(25%) will be assigned covering the readings and lectures.
Topical Outline
N.B.: Topics may change to follow class interest,
schedule outside speakers, accommodate unforeseen opportunities or
exigencies, etc.
Introduction: Computational molecular biology survey
Objects and Hierarchy 1: Atoms, Nucleotides, DNA, RNA, Amino Acids
Objects and Hierarchy 2: Genes, Chromosomes, Peptides, Proteins
Molecular biology databases: LiMB, GenBank, Swissprot, PDB,
CCD, Medline, etc.
Sequences 1: Sequence similarity; dynamic programming alignment
Sequences 2: Multiple alignments, phylogenetic trees, database searching
Sequence Patterns: Pattern matching, pattern induction
Gene Finding: Regulatory regions, intron/exon calling
Protein Structure Prediction: Homology modeling
Secondary Structure Prediction: various methods
Atomic Force Fields: functional form, parameterization, molecular mechanics
Protein Structure Prediction: fold recognition, sequence-structure alignment
Protein Structure Prediction: side-chain packing, loop placement
Rational Drug Design: docking
Rational Drug Discovery: QSAR, combinatorial methods
Genome map construction and sequencing
Forensic DNA
Computing with DNA
Project Presentations, Poster Session