Discovery at the Speed of Thought: Applying Advanced Analytics and Data Intensive Supercomputer Appliances to Shorten Discovery Cycles

The Data Intensive Discovery Initiative Di2 at the University at Buffalo (UB), SUNY is exploiting IBM Netezza’s Data Intensive Supercomputer (DISC) Analytic Appliance, Revolution Analytics R Enterprise and Fuzzy Logix’ DB Lytix in-database computation engine to shorten discovery cycles. The orders of magnitude faster computational performance and advanced analytics of the combined technology suite is helping researchers shorten discovery processes for determining the causes of disease; target identification; drug discovery; moving therapies through the approval process and increasing positive healthcare outcomes while reducing costs.  Presenters from Saturn Business Systems, UB, IBM Netezza, Fuzzy Logix, Revolution Analytics and Big Computing will share their actual experiences and the results of applying these extraordinary technologies to solve real world problems. Please join us and enjoy great food, cocktails and networking.

Agenda

• Introduction to Data Intensive Analytics: Overview of Big Data challenges scientists are facing and introduction of speakers
• Optimizing Disease Discovery at the Data Intensive Discovery Initiative (Di2) at the University at Buffalo, SUNY:  Overview of the Di2’s computational infrastructure and description of how Di2 scientists exploit Revolution R and Fuzzy Logix “in-database” algorithms to speed discovery.  Specific discussion regarding gene/environment interaction analysis for Multiple Sclerosis and the 147X speed up attained on the Di2’s IBM Netezza 1000/24
• Advanced Healthcare Discovery: Fuzzy Logix In-Database Advanced Statistical Library on the IBM Netezza Platform.  How Fuzzy Logix’ DB Lytix in-database computation engine is being used to deliver better healthcare outcomes at lower costs
• Revolution R Enterprise on IBM Netezza: Revolution R Enterprise framework (with R at its core) on IBM Netezza Analytics Appliances: How Revolution Analytics optimizes IBM Netezza and how IBM Netezza optimizes Revolution Analytics”
• Big Computing R Application Packages for BioPharma Discovery:  Overview of the BioPharma R Application Packages developed by the Big Computing Analytics Team and discussion of the impact to the discovery cycle
• Panel discussion/questions

Speakers

Murali Ramanathan, Professor of Pharmaceutical Sciences, University at Buffalo (UB), SUNY, and Co-Director of the Data Intensive Discovery Initiative at UB

Michael Upchurch, COO, Fuzzy Logix

Derek Norton, Solutions Executive, Revolution Analytics

Bill Zanine, Business Solutions Executive, Analytics Solutions at IBM Netezza

Richard Schultz, Director, Big Computing

Todd C. Scofield, Business Development Executive, Saturn Business Systems, and Founder Data Intensive Discovery Initiative at the University at Buffalo, SUNY

Kari Griffith, IBM Life Sciences Software Leader