Scalable, dynamic analysis and visualization for genomic datasets

Grant Wallace, Matthew Hibbs, Maitreya Dunham, Rachel Sealfon, Olga G. Troyanskaya, Kai Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A challenge in data analysis and visualization is to build new-generation software tools and systems to truly accelerate scientific discoveries. The recent focus of Princeton's next-generation software project is to investigate how to develop new-generation data analysis and visualization capabilities for genomic scientists to analyze high-throughput genomic dataseis. This paper describes the software tools we have recently developed to enable dynamic, large-scale data analysis and visualization of multiple dataseis on large-scale, high-resolution display wall systems. Our initial experience with the deployed tools at Princeton's Lewis-Sigler Institute for Integrative Genomics is very encouraging. Scientists can effectively learn new knowledge from multiple datasets, find new insights, and generate new hypotheses that are not possible with current methods.

Original languageEnglish (US)
Title of host publicationProceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM
DOIs
StatePublished - 2007
Event21st International Parallel and Distributed Processing Symposium, IPDPS 2007 - Long Beach, CA, United States
Duration: Mar 26 2007Mar 30 2007

Publication series

NameProceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM

Other

Other21st International Parallel and Distributed Processing Symposium, IPDPS 2007
CountryUnited States
CityLong Beach, CA
Period3/26/073/30/07

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Software
  • Mathematics(all)

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