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Please reply to this letter if you'd like to meet the speaker.

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                                CATS Seminar

                        Capital Area Theory Seminar

             http://www.umiacs.umd.edu/users/liberato/cats/

    Some Combinatorial Algorithms Problems in Hunting Disease Genes

			  Alejandro Schaffer
  			National Institutes of Health

                    Friday, May 7, 1999, 2 p.m.
                               AVW 4460
                          (Special room/time)
                 
                                  Abstract

One subspecialty of computational biology that has seen minimal
participation by computer scientists is disease gene hunting. This may
be because it is hard to get data and the problems appear to be more
statistical than combinatorial. Nevertheless, successful disease gene
hunting depends on carrying out various difficult computations on
family trees also known as pedigrees, which can be usefully viewed as
graphs. When the families come from an inbred population the pedigree
graphs are directed acyclic graphs, but not trees, and the
computations get more interesting from an algorithmic perspective. I
will explain a variety of combinatorial problems that arise in
analyzing pedigree graphs to find the approximate chromosomal location
of disease causing genes.  Three of these problems can be cast as
special cases of minimum vertex feedback set, single sorce shortest
paths, and Steiner tree, which are well known to algorithmicists.
Other pedigree graph problems may not be special cases of well-known
algorithms problems, but I hope to convince you that algorithmicists
may contribute to better solutions.

Includes joint work with Richa Agarwala (NIH), Leslie
Biesecker (NIH), Ann Becker (Technion), and Dan Geiger (Technion).



Contact: Vincenzo Liberatore (liberato@umiacs.umd.edu)

The Capital Area Theory Symposia is an NSF sponsored series of symposia in 
theoretical computer science bringing computer scientists from around 
the world to the Capital area. The Symposia are given at the 
University of Maryland in cooperation with the Computer Science Department 
and UMIACS. NSF support under grant CCR-9732907 is gratefully acknowledged