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September
2017
26
Ben Voight, PhD
New York Genome Center
4:00 PM — 5:30 PM

Computational Approaches to Identify Meaningful Complex Disease Loci in the Human Genome

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About

Associate Professor, Department of Systems Pharmacology and Translational Therapeutics and the Department of Genetics

 

University of Pennsylvania

 

“Computational approaches to identify meaningful complex disease loci in the Human Genome.”

 

Abstract: Thousands of associated loci for complex traits and diseases – hematopoietic traits, type 2 diabetes, heart disease, and beyond – are now available. However, leading associated variants implicate non-coding variation, a fact that has slowed progress on novel biological and therapeutic discoveries. Thus, a key challenge that has emerged is how to incorporate human genetic association data – coupled with other types of information – to identify the most biologically or therapeutically actionable loci from the “omnigenic” genetic architecture to deeply study.

 

To take on this challenge, Dr. Voight will describe his work using two types of computational strategies. The first considers the use of multi-phenotypes to ‘scan’ the genome to identify loci with consistent, localized, and synergistic directional evidence of disease. His lab’s leading analysis for type 2 diabetes and coronary heart disease will be presented. The second approach uses established loci for disease to build a model (penalized regression) to identify functional genomic regulatory features that predict these established sites. They demonstrate that our model outperforms competing functional prediction algorithms, with the benefit that the etiologically relevant features that are selected provide a modicum biological interpretability. Dr. Voight will discuss applications of the proposed approach to type 2 diabetes and platelet-related traits.

 

 

Biography: Ben Voight, PhD, received his PhD from the University of Chicago, advised by Drs. Jonathan Pritchard and Nancy Cox, focused on studies of natural selection and demographic inference in human populations.

 

As a postdoctoral fellow and research scientist from 2006-2011, Dr. Voight worked with Drs. David Altshuler and Mark Daly at Massachusetts General Hospital and the Broad Institute. There, he led development of computational pipelines and applications toward identifying common genetic variation associated complex phenotypes, particularly type 2 diabetes and heart disease, as well as application of the framework of Mendelian Randomization to perform causal inference using human genetics data.

 

He is currently an Associate Professor in the Department of Systems Pharmacology and Translational Therapeutics and the Department of Genetics at the University of Pennsylvania. He serves as vice-chair for the Genomics and Computational Biology Program there. In 2012, Dr. Voight was selected as an Alfred P. Sloan Foundation Fellow. He also recently received a Presidential Early Career Award for Scientists and Engineers.

 

Dr. Voight is a population geneticist and computational biologist whose research focuses on the burden and impact of complex disease, with the terminal aim of translating human genetic observations into targetable mechanisms, evolutionary insights, and new candidates for therapeutics development. Using his population and statistical genetics expertise, his lab develops computational methods and analyzes large-scale human genomics data to discern the evolutionary history and genetic basis of complex disease.

 

To read more about Dr. Ben Voight’s research, please visit: Google Scholar – Ben Voight, PhD

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