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HPC and grid computing for integrative biomedical research

  • Tahsin Kurc
  • , Shannon Hastings
  • , Vijay Kumar
  • , Stephen Langella
  • , Ashish Sharma
  • , Tony Pan
  • , Scott Oster
  • , David Ervin
  • , Justin Permar
  • , Sivaramakrishnan Narayanan
  • , Yolanda Gil
  • , Ewa Deelman
  • , Mary Hall
  • , Joel Saltz
  • Ohio State University
  • Emory University
  • University of Southern California
  • University of Utah

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Integrative biomedical research projects query, analyze, and integrate many different data types and make use of datasets obtained from measurements or simulations of structure and function at multiple biological scales. With the increasing availability of high-throughput and high-resolution instruments, the integrative biomedical research imposes many challenging requirements on software middleware systems. In this paper, we look at some of these requirements using example research pattern templates. We then discuss how middleware systems, which incorporate Grid and high-performance computing, could be employed to address the requirements.

Original languageEnglish
Pages (from-to)252-264
Number of pages13
JournalInternational Journal of High Performance Computing Applications
Volume23
Issue number3
DOIs
StatePublished - 2009

Keywords

  • Integrative biomedical research
  • Multi-scale integrative investigation
  • System level integrative analysis

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