UCLA Bioinformatics Program

Speaker:Serafim Batzoglou, Department of Computer Science,Stanford University

When: Mon, Nov 5, 4:00pm – 5:00pm

Where: 120 La Kretz

Abstract:
Genomics is rich with computational problems where algorithms and statistical methods can have a big impact on data analysis and biological discovery. Here, I will present three such problems. 1. Gene Finding. Given a sequenced genome, the first task is to find the genes. This core bioinformatics problem is still largely open. The set of human genes, for example, has not been finalized. Here, I will present CONTRAST, a gene finder based on a CRF/SVM approach, which is the first tool to show significant improvement in human gene finding by using multiple sequence alignments as informants. 2. Network Alignment. Protein association networks summarize our knowledge of which proteins work together in modules and networks to accomplish complex biological processes. Many global protein interaction networks have been predicted for organisms ranging from bacteria to human. Here, I will present Graemlin, a system for comparing networks across organisms and finding conserved modules – subgraphs of conserved proteins and their associations. 3. Ancestral Population Inference. Projects like HapMap provide whole-genome genotypes for diverse populations. Given a genotyped individual, using such datasets we may attempt to predict the allele-specific population source of the individual’s chromosomes. I will present HAPAA, a tool for accomplishing this task. Then, I will show that ancestry inference can accurately extract the source populations of admixtures that happened as far as 20 generations ago, covering much of the modern history of population movements.

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