Computer Science - Seminar Event
Location: Torgerson 2150The speaker is Dr. David Mittleman, Virginia Bioinformatics Institute, Virginia Tech. The abstract of his talk is the following: Genome-scale sequencing technologies promise to revolutionize our understanding of genetics, evolution, and disease by making it feasible to survey a much broader spectrum of sequence variation on a population scale. However, this potential can only be realized insofar as methods for extracting and interpreting all forms of variation from these new data types can be established. The error profiles and read length limitations of early versions of next-gen technologies rendered them ineffective for some sequence variant types, particularly indels (loss or gain of DNA bases; and DNA repeats). This has fostered the general misconception that such variants are inherently inaccessible to these sequencing platforms. At the same time, these variations have emerged as leading candidates for “missing heritability” in association studies. Sensitive identification of these variants in large-scale next-gen sequencing efforts will enable comprehensive genotype-phenotype studies capable of revealing previously invisible associations. In this talk, I will present a case study of how we derive mutation information from whole-genome data and discuss the emerging challenges in personal genomics. While the costs and throughputs of sequencing have continued to improve, analysis of genetic variation from whole-genome data continues to be a technical and financial challenge, requiring ever-larger computer systems to manage the increasingly intensive computational demands. There is a great opportunity for computer scientists and mathematicians to join the cause and help make sense of this growing source of biological data.
Contact: T. M. Murali
Email: murali@cs.vt.edu
Phone: 5402318534