Skip to main content
Article
HPC Enabled Data Analytics for High-Throughput High-Content Cellular Analysis
Computer Science and Engineering Faculty Publications
  • Ross A. Smith
  • Rhonda J. Vickery
  • Jack Harris
  • Sara Gharabaghi, Wright State University - Main Campus
  • Thomas Wischgoll, Wright State University - Main Campus
  • David Short, Wright State University - Main Campus
  • Robert Trevino
  • Steven A. Kawamoto
  • Thomas J. Lamkin
  • Kevin Schoen
  • Eric E. Bardes
  • Scott C. Tabar
  • Bruce J. Aronow
Document Type
Conference Proceeding
Publication Date
1-1-2016
Disciplines
Abstract

Biologists doing high-throughput high-content cellular analysis are generally not computer scientists or high performance computing (HPC) experts, and they want their workflow to support their science without having to be. We describe a new HPC enabled data analytics workflow with a web interface, HPC pipeline for analysis, and both traditional and new analytics tools to help them transition from a single workstation mode of operation to power HPC users. This allows the processing of multiple plates over a short period of time to ensure timely query and analysis to match potential countermeasures to individual responses.

Comments

The International Conference for High Performance Computing, Networking, Storage, and Analysis, November, 13-18, 2016, Salt Lake City, UT.

Citation Information
Ross A. Smith, Rhonda J. Vickery, Jack Harris, Sara Gharabaghi, et al.. "HPC Enabled Data Analytics for High-Throughput High-Content Cellular Analysis" (2016)
Available at: http://works.bepress.com/thomas_wischgoll/88/