[Bioperl-l] 2003 CSHL Computational Genomics Course

[William R. Pearson]

I would like to encourage the BioPerl community to consider attending
the 2003 Cold Spring Harbor Computational Genomics Course.  Cold
Spring Harbor runs two courses in the Bioinformatics/Computational
Biology area, Lincoln Stein's Bioinformatics Programming course, and
the Computational Genomics Course.  The Computational Genomics Course
focusses more on algorithms for analysing sequences (you will learn A
LOT about sequence comparison, similarity statistics, motif finding,
and other large-scale approaches), and about genome databases and,
this year, comparative genomics.

I have been very impressed by the effort that the BioPerl community
has put into making various software packages and algorithms
interoperable. But currently, there appears to be a division of labor
between bioinformatics folks, who make things work together, and
computational biology folks, who develop new algorithms.  I think
there are new algorithms and new statistical approaches to be
developed, and the BioPerl community might enjoy developing these new
approaches.  To do that, one needs a deeper understanding of the
algorithmic and statistical foundations of current methods, which is
what the Computational Genomics Course provides.

For additional information and the lecture schedule and problem sets
for the 2002 course, see:

	http://www.people.virginia.edu/~wrp/cshl02

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

	http://meetings.cshl.org/course_app.htm

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Course announcement - Application deadline, July 15, 2003

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Cold Spring Harbor
COMPUTATIONAL GENOMICS
NOVEMBER 5 - 11, 2003

INSTRUCTORS:

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.

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Bill Pearson