Mathematical and Computational Approaches in High-Throughput Genomics

September 12 - December 16, 2011


Biological sciences have been transformed over the past two decades by the development of technologies capable of performing large-scale measurements of cellular states. In particular, DNA sequencing instruments have undergone an extraordinary increase in efficiency during the past few years that has reduced the time and cost required to sequence billions of bases by several orders of magnitude. This is revolutionizing the scale and potential applications of genomic studies, and creating an enormous need to develop mathematical and computational infrastructures to meet emerging data analysis challenges. To name just a few examples, applications requiring the development of novel mathematical and statistical frameworks include the reconstruction of RNA transcript populations, identifying sequence variations (both single-nucleotide and segmental) and exploring their disease associations, locating the sites of protein-DNA interactions, elucidating population histories, and reconstructing microbial communities that colonize particular hosts or environmental niches. The goal of this long program is to bring together mathematical and computational scientists, sequencing technology developers in both industry and academia, and the biologists who use the instruments for particular research applications. This presents a unique opportunity to foster interactions between these three communities over an extended period of time and advance the mathematical foundations of this exciting field.

Organizing Committee

Eleazar Eskin (University of California, Los Angeles (UCLA), Computer Science)
Phil Green (University of Washington)
Stanley Nelson (University of California, Los Angeles (UCLA))
Lior Pachter (University of California, Berkeley (UC Berkeley))
Matteo Pellegrini, Chair (University of California, Los Angeles (UCLA), Molecular, Cell, and Developmental Biology)
Sebastien Roch (University of California, Los Angeles (UCLA), Mathematics)
Eric Schadt (Pacific Biosciences)
Elizabeth Thompson (University of Washington)
Wing Wong (Stanford University)