Genomic Analytics Identify MS Trends

| May 9, 2012

 Genomic Analytics Identify MS Trends, by Dan Gatti, Big Data I/O Forum

 Analytics is leading the way to help researches at University of Buffalo developing algorithms  for big data containing genomic datasets to help them uncover critical factors that speed up disease progression in MS patients. This is a complex task, however, given the size and diversity of the data.

According to Dr. Murali Ramanathan, Lead Researcher at SUNY Buffalo. “Identifying common trends across massive amounts of MS data is a monumental task that is much like trying to shoot a speeding bullet out of the sky with another bullet.”

Researchers at The State University of New York at Buffalo are using advanced analytics to comb through a series of over 2,000 genetic and environmental factors that might lead to multiple sclerosis (MS) symptoms.

What this means is that on the research side, this is the first time that it has been possible to explore clinical and patient data to find hidden trends among MS patients by looking at factors such as gender, geography, ethnicity, diet, exercise, sun exposure, and living and working conditions.

The big data including medical records, lab results, MRI scans and patient surveys, arrives in various formats and sizes, requiring researchers to spend days making it manageable before they can analyze it.  

Research interests are in the area of treatment of multiple sclerosis (MS), an inflammatory-demyelinating disease of the central nervous system that affects over 1 million patients worldwide.  MS is a complex, variable disease that causes physical and cognitive disability and nearly 50% if patients diagnosed with MS are unable to walk after 15 years.  The etiology and pathogenesis of MS remains poorly understood.  The focus of the research is to identify the molecular mechanisms by which the autoimmunity of MS is translated into neurological damage in the CNS.

Dr. Ramanathan’s group at the University at Buffalo works on the role of gene-environment interactions in MS disease progression. The goal is to help elucidate the of understanding the molecular mechanisms of the MS disease process and of MS treatments. He works with strong collaborative team that includes Drs. Bianca Weinstock-Guttman (Director of the Baird MS Center), Robert Zivadinov (Director, Buffalo Neuroimaging Analysis Center) and Vipin Chaudhary (Director, Data Intensive Discovery Initiative0

 Dr. Murali Ramanathan is an Professor of Pharmaceutical Sciences and Neurology at the State University of New York at Buffalo.  He joined the Department of Pharmaceutical Sciences in 1994. He received his B.Tech. (Honors) in Chemical Engineering

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