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Gaining Insights in Multiple Sclerosis by Causal Network Analysis

Network methods can reveal insights into disease biology and have been successfully applied to a variety of datasets. A particular field of network inference is causal inference, which focuses on inference that differentiates between likely causal and likely reactive relationships among variables, resulting in greater parsimony and biological relevance of the findings. In this webinar, Dr. Hayete presented the application of GNS Healthcare’s proprietary causal inference platform to the Orion MS dataset, discussing both the methodology and the generated findings.

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Webinar originally hosted April 30, 2015 at 12pm ET
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About Dr. Boris Hayete

As Senior Director of Genomic Medicine at GNS Healthcare, Boris Hayete, PhD, leads a scientific team focusing on systems biology and related areas. He has coauthored a number of peer-reviewed articles on systems biology and has developed a widely used network inference algorithm.

Dr. Hayete has more than a decade of experience in network inference and systems biology; he has been at GNS Healthcare for over 7 years and was previously at the Boston University Bioinformatics PhD program. Prior to earning his PhD, Dr. Hayete conducted research and applied work in web search, and he has a bachelor’s degree and master’s degree in computer science with a focus on machine learning and natural language processing from the Johns Hopkins University.

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