Events - Weekly
|Sunday, April 13|
|Monday, April 14|
Massimo Vergassola, UCSD, Finding the needle in a biological haystack
Early T-cell activation is selected by evolution to discriminate a few foreign peptides rapidly from a vast excess of self-peptides, and it is unclear in quantitative terms how this is possible. It will be discussed how a generic proofreading cascade supplemented by a single negative feedback accounts quantitatively for early T-cell activation, including antagonistic effects. Modulation of the negative feedback mediated by the SHP-1 phosphatase explains previous counterintuitive observations and new experiments validate predictions. Absolute limits on the tradeoffs between decision speed and accuracy are then explored. In addition to the immune system, rapidly developing embryos, and cellular response to stress, provide examples where fast and accurate actions are required. Statistical theory under the rubric of 'exploit-explore' supplies rigorous performance bounds and algorithms that realize them. It will be shown that common protein phosphorylation networks can implement optimal decision theory algorithms, and speculated that the ubiquitous chemical modifications to receptors during signaling actually perform such analogue computations.
Joseph Henry Room, Jadwin Hall · 12:00 p.m.– 1:00 p.m.
|Tuesday, April 15|
Steven Salzberg, Johns Hopkins University School of Medicine, Computational Challenges of High Throughput Genome Sequence Analysis
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.
Lewis Thomas Lab 003 · 4:00 p.m.– 5:00 p.m.
|Wednesday, April 16|
|Thursday, April 17|
|Friday, April 18|
|Saturday, April 19|