Biological Sequence Analysis and Probabilistic Models
This meeting brought together leaders from several areas of biological sequence analysis, with an emphasis on advancing the underlying theoretical models that many problems share. Topics included recognition of DNA cis-regulatory elements; evolutionary approaches for remote homology detection; analysis of next-gen sequencing data for functional genomics; and combined phylogenetic and population genetic models for studying sequence evolution.
Organizers
Sean Eddy, Janelia/HHMI
Katherine Pollard, University of California, San Francisco
Adam Siepel, Cornell University
Invited Participants
Serafim Batzoglou, Stanford University
Mathieu Blanchette, McGill University
Graham Coop, University of California, Davis
Richard Durbin, Wellcome Trust Sanger Institute
Barbara Englehardt, Duke University
Manolo Gouy, CNRS - Lyon
Philip Green, University of Washington
David Haussler, HHMI/University of California, Santa Cruz
Jotun Hein, University of Oxford
Asger Hobolth, Aarhus University
Ian Holmes, University of California, Berkeley
Curtis Huttenhower, Harvard School of Public Health
Anders Krogh, University of Copenhagen
Christopher Langmead, Carnegie Mellon University
Ari Löytynoja, Institute of Biotechnology, University of Helsinki
Gerton Lunter, University of Oxford
Rasmus Nielsen, University of California, Berkeley
Uwe Ohler, Duke University
Ivan Ovcharenko, National Institutes of Health
Elena Rivas, Janelia/HHMI
Ingo Ruczinski, Johns Hopkins University
Mikkel Schierup, Aarhus University
Saurabh Sinha, University of Illinois
Johannes Soeding, University of Munich
Yun Song, University of California, Berkeley
Marc Suchard, University of California, Los Angeles
Olga Troyanskaya, Princeton University
Tandy Warnow, University of Texas at Austin
