State University of New York at Buffalo

Substantial data analysis improves gene-environmental correlation identification to help develop new treatment for multiple sclerosis

Published on 25-Jul-2013

"IBM analytics help our researchers fine-tune their aim and match the speed of analysis with the rate of data coming into our systems. Our goal is to demystify why the disease progresses more rapidly in some patients and get those insights back to other researchers, so they can find new treatments." - Dr. Murali Ramanathan, research lead

Customer:
State University of New York at Buffalo

Industry:
Education

Deployment country:
United States

Solution:
Big Data, Big Data & Analytics, Big Data & Analytics: Operations/Fraud/Threats, Data Warehouse, Smarter Computing, Smarter Planet

IBM Business Partner:
Revolution Analytics

Overview

The State University of New York (SUNY) at Buffalo is the largest university system in the United States and home to one of the leading multiple sclerosis (MS) research centers in the world. Founded in 1816, SUNY offers more than 7,500 degree programs, has over 60 campuses in New York and enrolls approximately 467,000 students.

Business need:
As one of the leading multiple sclerosis (MS) research centers in the world, researchers at SUNY Buffalo wanted to identify and understand environmental factors that may contribute to MS.

Solution:
SUNY Buffalo researchers use a powerful solution that combines data warehouse and analytic capabilities to handle the exponential growth rate of genetic variations involved in breakthrough data-mining methods for gene interaction in disease discovery for MS.

Benefits:
·Reduces the time required to conduct gene-environmental interactions analysis by 99 percent, from 27.2 hours to 11.7 minutes

Case Study

The State University of New York (SUNY) at Buffalo is the largest university system in the United States and home to one of the leading multiple sclerosis (MS) research centers in the world. Founded in 1816, SUNY offers more than 7,500 degree programs, has over 60 campuses in New York and enrolls approximately 467,000 students.

The Opportunity
As one of the leading multiple sclerosis (MS) research centers in the world, researchers at SUNY Buffalo wanted to identify and understand environmental factors that may contribute to MS. However, gene-environmental research presented researchers with enormous volumes of data for which they needed high-performance processing power and speed to make meaningful, publishable discoveries.

What Makes It Smarter
A major challenge in gene interaction research is analyzing the explosions of immense data sets at a speed that will help save lives. SUNY Buffalo researchers use a powerful solution that combines data warehouse and analytic capabilities to handle the exponential growth rate of genetic variations involved in breakthrough data-mining methods for gene interaction in disease discovery for MS. The solution helps enable researchers to use new algorithms and analyze volumes of data that could number in the quintillions, which was previously impossible, allowing them to examine more than 2,000 genetic and environmental factors that may contribute to the development and progression of MS. For example, researchers can analyze vitamin D metabolites’ protective associations with disability and brain atrophy in MS and its possible correlation to why MS is more common in northern latitudes and less common toward the equator. And in turn, new insights can help develop therapeutic and prevention strategies for treating and managing MS.

Real Business Results
· Reduces the time required to conduct gene-environmental interactions analysis by 99 percent, from 27.2 hours to 11.7 minutes
· Facilitates new findings and breakthroughs, allowing research scientists to publish multiple articles in scientific journals
· Helps enable studies requiring more complex variables such as vector phenotypes, giving researchers the ability to speed computations and increase data sets


For More Information
Please contact your IBM representative or IBM Business Partner. Visit us at ibm.com/software/data/netezza.

To learn more about State University of New York at Buffalo, visit http://www.buffalo.edu.

Products and services used

IBM products and services that were used in this case study.

Software:
IBM Netezza Analytics, IBM Netezza 1000

Legal Information

© Copyright IBM Corporation 2013 IBM Corporation Software Group Route 100 Somers, NY 10589 Produced in the United States of America May 2013 IBM, the IBM logo, ibm.com and Netezza are trademarks of International Business Machines Corp., registered in many jurisdictions worldwide. Other product and service names might be trademarks of IBM or other companies. A current list of IBM trademarks is available on the Web at “Copyright and trademark information” at www.ibm.com/legal/copytrade.shtml This document is current as of the initial date of publication and may be changed by IBM at any time. Not all offerings are available in every country in which IBM operates. The performance data discussed herein is presented as derived under specific operating conditions. Actual results may vary. THE INFORMATION IN THIS DOCUMENT IS PROVIDED “AS IS” WITHOUT ANY WARRANTY, EXPRESS OR IMPLIED, INCLUDING WITHOUT ANY WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND ANY WARRANTY OR CONDITION OF NON-INFRINGEMENT. IBM products are warranted according to the terms and conditions of the agreements under which they are provided.


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