 |
CSE Bioinformatics Steering Committee:
Ramamohan Paturi, Co-Chair Bioinformatics Steering Committee
Pavel Pevzner, CSE Faculty
Vineet Bafna, CSE Faculty
Viera Kair, CSE Undergraduate Advisor
Patricia Raczka, CSE Undergraduate Program Director and Advisor
Questions about information found on this page may be directed to Patricia Raczka at 858/534-3621
or to
raczka@cs.ucsd.edu
| Course Number |
Title |
Fall Quarter 2007 |
Winter Quarter 2008 |
Spring Spring 2008 |
| BILD 94 |
Professional Issues in Bioinformatics (http://www-cse.ucsd.edu/classes/sp06/bild94) |
- |
- |
Staff - BioEngr Dept |
| CSE 181/ BIMM 181/ BENG 181 |
Molecular Sequence Analaysis |
- |
- |
Pavel Pevzner - CSE Dept |
| CSE 182/ BIMM 182/ BENG 182/CHEM 182 |
Biological Databases |
Vineet Bafna - CSE Dept |
- |
- |
| BENG 183 |
Applied Genomic Technologies |
Trey Ideker - BioEngr Dept |
- |
- |
| CSE 184/ BIMM 184/ BENG 184 |
Computational Molecular Biology |
- |
Wei Wang - Chem Dept |
- |
| BIMM 185 |
Bioinformatics Lab |
- |
- |
Steven Briggs - Biol Dept |
| Math 186 |
Probability and Statistics |
- |
Glenn Tesler - Math Dept |
- |
| CSE 191 |
Seminar in CSE: Bioinformatics |
- |
Cancelled |
- |
Bioinformatics Course History
BILD 94
Spring 2008, Staff, BioEngr Dept.
Spring 2007, Vineet Bafna, CSE Dept.
Spring 2006, Vineet Bafna, CSE Dept.
Spring 2005,William Loomis, Biol Dept.
CSE 181/BIMM 181/BENG 181/CHEM 181
Spring 2008, Pavel Pevzner, CSE Dept.
Spring 2007, Pavel Pevzner, CSE Dept.
Spring 2006, Pavel Pevzner, CSE Dept.
Spring 2005, Pavel Pevzner, CSE Dept.
Fall 2005, Phillip Bourne,Chem Dept.
Spring 2004, Pavel Pevzner, CSE Dept.
Spring 2003, Pavel Pevzner, CSE Dept.
CSE 182/BIMM 182/BENG 182/CHEM 182
Fall 2007, Vineet Bafna, CSE Dept.
Fall 2006, Vineet Bafna, CSE Dept.
Fall 2005, Vineet Bafna, CSE Dept.
Fall 2004, Vineet Bafna, CSE Dept.
Fall 2003, Phillip Bourne as Pharm 201, Pharm Sch
Spring 2004, Vineet Bafna, CSE Dept.
BENG 183
Fall 2007, Tre Ideker, Bioengr Dept.
Fall 2006, Tre Ideker, Bioengr Dept.
Fall 2005, Tre Ideker, Bioengr Dept.
Fall 2004, Tre Ideker, Bioengr Dept.
Winter 2004, Michael Heller, Bioengr Dept.
CSE 184/BIMM 184/BENG 184/CHEM 184
Winter 2008, Wei Wang,Chem Dept.
Winter 2007, Wei Wang,Chem Dept.
Winter 2006, Wei Wang,Chem Dept.
Winter 2005, Steven Cammer,Chem Dept.
Winter 2004, Steven Cammer, Chem Dept.
BIMM 185
Spring 2008, Steven Briggs, Biol Dept.
Spring 2007, Steven Briggs, Biol Dept.
Spring 2006, William Loomis, Biol Dept.
Spring 2004, William Loomis, Biol Dept.
Math 186
Winter 2008, Glenn Tesler, Math Dept.
Winter 2007, Glenn Tesler, Math Dept.
Winter 2006, Glenn Tesler, Math Dept.
Winter 2004, Glenn Tesler, Math Dept.
Winter 2003, Leonard Haff, Math Dept.
Courses for the Bioinformatics Program:
BILD 94 (1 unit): This seminar will introduce undergraduate students, expecially freshmen
and sophomores, to a variety of issues and topics in the field of informatics.
CSE 181/ BIMM 181/BENG 181 - Molecular Sequence Analysis (4 units):
This course covers the analysis of nucleic acid and protein sequences, with
an emphasis on the application of algorithms to biological problems.
Topics include sequence alignments, database searching, comparative genomics,
and phylogenetic and clustering analyses. Pairwise alignment,
Multiple alignment, DNA sequencing, Scoring functions, Fast database search,
Comparative genomics, Clustering, Phylogenetic trees, Gene
finding/DNA statistics. Prerequisites: CSE 100 or Math 176, CSE 101 or Math 188, BIMM 100
or Chem 114D
CSE 182 /BIMM 182/BENG 182/CHEM 182 - Biological Databases (4 units):
This course provides an introduction to the features of biological data,
how that data are organized efficiently in databases, and how existing data
resources can be utilized to solve a variety of biological problems.
Relational databases, Object oriented data bases, Ontologies, Data modeling and
description, Survey of current biological database with respect to above,
Implementation of a database focused on a biological topic. Prerequisites:
CSE 100 or Math 176
BENG 183 - Applied Genomic Technologies (4 units):
The goal of this course is to introduce the student to fundamental principles
and enabling technologies that will be utilized for
harnessing genomic information for biomedical applications. Technologies will
be introduced progressively, from DNA to RNA to
protein to whole cell platforms. The integration of biology, chemistry,
engineering, and computation will be stressed. Topics
include: Technology for the Genome, DNA Chips, RNA Technologies, Proteomic
Technologies, Cellomic Technologies, Analyzing
Cell Function. Prerequisites: BIMM100 or Chem114D, BICD110
CSE 184/BIMM 184/BENG 184 - Computational Molecular Biology (4 units):
This advanced course covers the application of machine learning and modeling
techniques to biological systems. Topics include gene structure,
recognition of DNA and protein sequence patterns, classification, and protein
structure prediction. Pattern discovery, Hidden Markov models/Support
vector machines/Neural network/profiles, Protein structure prediction,
Functional characterization of proteins, Functional genomics/proteomics,
Metabolic pathways/gene networks. Prerequisites: BIOINF 181, 182. Bioinformatics majors only.
BIMM 185 - Bioinformatics Lab (4 units):
This course emphasizes the hands-on application of bioinformatics methods to
biological problems. Students will gain experience in the application of
existing software, as well as in combining approaches to answer specific
biological questions. Sequence alignment, Fast database search, Profiles and
motifs, Comparative genomics, Gene finding , Phylogenetic trees, Protein
structure, Functional characterization of proteins, Expression analysis,
Computational proteomics. Prerequisites: Two courses out of BIOINF 181,
BIOINF 182, BIOINF 183, BIOINF 184. Bioinformatics majors only.
Math 186 - Probability and Statistics (4 units):
This course will cover an introduction to probability and statistics,
the use of discrete and random variables, different types of distributions, data
analysis and inferential statistics, likelihood estimates and scoring
matrices with applications to biological problems. Introduction to probability,
Discrete and continuous random variables, Binomial, Poisson, and Gaussian
distributions, Central limit theorem, Data analysis and inferential statistics,
Likelihood estimators and scoring matrices, Applications to sequence and
functional analysis of genomes and genetic epidemiology. Prerequisites:
Math 20A, Math 20B, Math 21C. Bioinformatics majors only.
 |  |