CSHL Computational Genomics Course

William R. Pearson wrp at alpha10.bioch.virginia.edu
Tue Jul 13 06:28:57 EST 2004

Course announcement - Application deadline, July 15, 2004


Cold Spring Harbor
NOVEMBER 5 - 11, 2003


Pearson, William, Ph.D., University of Virginia, Charlottesville, VA
Smith, Randall, Ph.D., SmithKline Beecham Pharmaceuticals, King of
Prussia, PA

Beyond BLAST and FASTA - This course presents a comprehensive overview
of the theory and practice of computational methods for gene
identification and characterization from DNA sequence data. The course
focuses on approaches for extracting the maximum amount of information
from protein and DNA sequence similarity through sequence database
searches, statistical analysis, and multiple sequence
alignment. Additional topics include gene recognition (exon/intron
prediction), identifying signals in unaligned sequences, and
integration of genetic and sequence information in biological
databases. The course combines lectures with hands-on exercises;
students are encouraged to pose challenging sequence analysis problems
using their own data. The course makes extensive use of local WWW
pages to present problem sets and the computing tools to solve
them. Students use Windows and Mac workstations attached to a UNIX
server; participants should be comfortable using the Unix operating
system and a Unix text editor.

The course is designed for biologists seeking advanced training in
biological sequence analysis, computational biology core resource
directors and staff, and for scientists in other disciplines, such as
computer science, who wish to survey current research problems in
biological sequence analysis.

The primary focus of the Computational Genomics Course is the theory
and practice of algorithms used in computational biology, with the
goal of using current methods more effectively and developing new
algorithms. Students more interested in the practical aspects of
software development are encouraged to apply to the Cold Spring Harbor
Bioinformatics - Writing Software for Genome Research Course.

For additional information and the lecture schedule and problem sets
for the 2003 course, see:



To apply to the course, fill out the form at:



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