Computing in the Life Sciences

1. Computing in the Life Sciences Simon Mercer Program Manager External Research & Programs Microsoft Research

2. The future can take even very smart people by surprise “It would appear that we have reached the limits of what is possible to achieve with computer technology, although one should be careful with such statements, as they tend to sound pretty silly in five years.” John von Neumann, 1949

3. Basic Research  Agility • Basic research group allows a company like Microsoft to respond more rapidly to change • Research provides a reservoir of technology, expertise and people that can be quickly brought to bear: • New technologies • New competitors • New business models

4. Augmenting In-House Research In-House Research • Central to Company Interests • Complete IP ownership • Expensive External Research • Closer to an “Open Innovation” model • Can explore long term goals and those peripheral to the current business • Risk profile can be higher – Failure is an Option Henry Chesbrough - Open Innovation: The New Imperative for Creating and Profiting from Technology, Harvard Business School Press, 2003

5. “There are things that other people get to before us. We avoid that a lot by working well with the universities. We have way bigger university outreach program than any company and that's worldwide, universities in Europe, India, China. The US universities are where we get the most out of that, but we want to make sure we're doing it everywhere.” – Bill Gates, Time Magazine interview, March 2006

6. Collaboration Model Accelerate Research CentersInstitutes Projects Validate Directions Explore Ideas Workshops & RFPs Supporting Programs – Faculty Summit, Ph.D. fellowships, New Faculty Awards, Ecosystem engagements

7. Activities • eScience Workshops 2004/5 • 60+ speakers • 120+ attendees • Seven countries represented • eScience Workshop 2006 (TBC) • eResearch Institute at Queensland University of Technology (TBC)

8. Projects 37 projects in 9 countries • Bioinformatics • Smart Clients for eSciencesWorkbenches that handle scientific data acquisition, management, integration, access, and visualization • Web services that unlock valuable data sets

9. Computational Science Function Express Gold: A caBIG Grid-aware Microarray Analysis Application The cancer Biomedical Informatics Grid (caBIG) develops applications to facilitate individual steps involved in microarray analysis, but there is no single application that leverages these tools in a user-friendly graphical interface.  We will develop a grid-aware microarray analysis application producing results which may be visualized using a rich set of viewers such as literature-based gene networks, pathways browsers, graphs, and heat maps. This tool will serve as a powerful means to identify previously underappreciated pathways for potential new targeted therapeutics.  Rakesh Nagarajan Washington University Siteman Cancer Center

10. Computational Science Advanced Biomedical Computing Systems for Cancer Research In collaboration with Winship Cancer Institute, the group is developing a computation-based cancer research system. The system consists of databases, cluster-based computing, and immersive visualization. With this system, they will be able to integrate large amounts of genomic, proteomic, and molecular/organ imaging data obtained from cultured cancer cells, clinical tissue specimens, and solid tumors to analyze and guide clinical cancer research. PIC:Picture May Wang Georgia Institute of Technology The Wallace H. Coulter Department of Biomedical Engineering

11. Computational Science OR-Eye A secure, reliable, and scalable distributed application that enables remote reviewing of the OR component of the pre-recorded electronic anesthesia record from any location where access to the Intranet/Internet is available. OR-Eye is now a fully developed, tested, and piloted product. OR-Eye2 is designed to completely replace the paper based anesthesia record with an electronic version. PIC:Picture Furrukh Khan The Ohio State University

12. Computational Science The Gateway to Biological Pathways Developing a Web application called “The Gateway to Biological Pathways” to aggregate and unify the existing pathway databases and provide Web services for querying the aggregated datasets based upon the open standard for pathway data interchange BioPAX Level 1. PIC:Picture Keyuan Jiang Purdue University, Calumet Information Systems and Computer Programming

13. Computational Science Web Service Access to Streaming NEXRAD Level II Radar Data Linked Environments for Atmospheric Discovery (LEAD), an NSF funded large scale cyberinfrastructure for severe storm forecasting, aims to improve access through a grid service architecture to enable access to data products, services, and processes for the severe storm researcher and educator. PIC:Picture Beth Plale Indiana University at Bloomington Computer Science

14. Computational Science Computational Tools for Population Biology An intrinsic characteristic of societies is their continual change, yet few analysis methods are explicitly dynamic. Our goal is to develop a novel conceptual and computational framework to accurately describe the social context of an individual at time scales matching changes in individual and group activity. Finding patterns of social interaction within a population has applications from epidemiology and marketing to conservation biology and behavioral ecology. Tanya Berger-Wolf University of Illinois at Chicago Electrical Engineering and Computer Science

15. Computational Science Piccolo.NET General purpose toolkit, useful for Information Visualization studies, Zooming User Interfaces, and other dynamic UI projects. Fully-accelerated through managed DirectX 9. For Mobile Devices, developers can use PocketPiccolo.NET, built on the .NET Compact Framework. Benjamin Bederson Aaron Clamage University of Maryland Human-Computer Interaction Lab

16. Computational Science Notebook Project The Notebook application is a client-side data repository, collaboration environment, and smart client for SOAP-based Web services. The application is designed to store data from Internet Web sessions and also enables researchers to annotate data locally. PIC:Picture Greg Quinn University of California at San Diego San Diego Supercomputer Center (SDSC)

17. Computational Science iCampus: OpenWetWare OpenWetWare (http://openwetware.org) is an effort to promote the sharing of information, know-how, and ideas among researchers and groups who are working in biology, biological engineering, and related disciplines. By providing a user-friendly editing interface (a wiki), the site provides a place for researchers to organize information and to collaborate with other community members. As of May, 2006, more than 50 academic labs from 25 institutions have joined the OpenWetWare community. Jason Kelly Massachusetts Institute of Technology Biological Engineering

18. Synthetic Biology RFP • “Design and fabrication of biological components and systems that do not already exist in the natural world” • “Re-design and fabrication of existing biological systems” www.syntheticbiology.org Synthetic Biology offers: • Great potential • Fertile collaboration

19. http://research.microsoft.com/compsci/

20. © 2006 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.