[Ml-stat-talks] Steven Salzberg special seminar today at 4:00 pm in LTL 003

Storey, John D. jstorey at Princeton.EDU
Tue Apr 15 13:58:14 EDT 2014

Here is a talk by one of the bona fide leaders of “Big Data”, today at 4:00pm in Lewis Thomas Lab 003.  In the past several years the cost of DNA sequencing has been drastically reduced.  The bottleneck in time and costs quickly became processing the raw data.  The work of Steven and his students has revolutionized our computational capabilities in processing raw sequencing data.  Steven is truly on the frontier of “Big Data” science, not hype but very real results and measurable impact.

Subject:  Steven Salzberg special seminar today at 4:00 pm

Steven Salzberg, Johns Hopkins University School of Medicine, Computational Challenges of High Throughput Genome Sequence Analysis<http://www.princeton.edu/genomics/seminars/special-seminars/viewevent.xml?id=227>
Apr 15, 2014, 4:00 p.m.
Lewis Thomas Lab 003
Next-generation sequencing technology allows us to peer inside the cell in exquisite detail, revealing new insights into biology, evolution, and disease that would have been impossible to discover just a few years ago. The enormous volumes of data produced by NGS experiments present many computational challenges that we are working to address. In this talk, I will discuss some of our algorithmic solutions to two key alignment problems: (1) mapping sequences onto the human genome at very high speed, and (2) mapping and assembling transcripts from RNA-seq experiments. I will also discuss some of the problems that can arise during analysis of exome data, in which the gene-containing portions of the genome are sequenced in an effort to identify mutations responsible for disease. My group has developed algorithms to solve each of these problems, including the widely-used Bowtie program for fast DNA sequence alignment, the TopHat and Cufflinks programs for assembly of genes from transcriptome sequencing (RNA-seq) experiments, and the new DIAMUND program for detecting de novo mutations. This talk describes joint work with current and former lab members including Ben Langmead, Cole Trapnell, Daehwan Kim, Mihaela Pertea, and Geo Pertea.

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