HPC Enabled Data Analytics for High-Throughput High-Content Cellular Analysis

Ross A. Smith; Rhonda J. Vickery; Jack Harris; Sara Gharabaghi; Thomas Wischgoll; David Short; Robert Trevino; Steven A. Kawamoto; Thomas J. Lamkin; Kevin Schoen; Eric E. Bardes; Scott C. Tabar; Bruce J. Aronow

HPC Enabled Data Analytics for High-Throughput High-Content Cellular Analysis

Ross A. Smith
, Rhonda J. Vickery
, Jack Harris
, Sara Gharabaghi
, Thomas Wischgoll
, David Short
, Robert Trevino
, Steven A. Kawamoto
, Thomas J. Lamkin
, Kevin Schoen
, Eric E. Bardes
, Scott C. Tabar
, Bruce J. Aronow

Computer Science and Engineering

Research output: Contribution to journal › Article › peer-review

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.

Original language	American English
Journal	Default journal
State	Published - Jan 1 2016

Keywords

Analytics
High-Throughput High-Content Screening
Pipeline
Visualization

Disciplines

Computer Sciences
Engineering

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HPC Enabled Data Analytics for High-Throughput High-Content CelluFinal published version, 893 KBLicense: Unspecified

Cite this

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title = "HPC Enabled Data Analytics for High-Throughput High-Content Cellular Analysis",

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.",

keywords = "Analytics, High-Throughput High-Content Screening, Pipeline, Visualization",

author = "Smith, \{Ross A.\} and Vickery, \{Rhonda J.\} and Jack Harris and Sara Gharabaghi and Thomas Wischgoll and David Short and Robert Trevino and Kawamoto, \{Steven A.\} and Lamkin, \{Thomas J.\} and Kevin Schoen and Bardes, \{Eric E.\} and Tabar, \{Scott C.\} and Aronow, \{Bruce J.\}",

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T1 - HPC Enabled Data Analytics for High-Throughput High-Content Cellular Analysis

AU - Smith, Ross A.

AU - Vickery, Rhonda J.

AU - Harris, Jack

AU - Gharabaghi, Sara

AU - Wischgoll, Thomas

AU - Short, David

AU - Trevino, Robert

AU - Kawamoto, Steven A.

AU - Lamkin, Thomas J.

AU - Schoen, Kevin

AU - Bardes, Eric E.

AU - Tabar, Scott C.

AU - Aronow, Bruce J.

PY - 2016/1/1

Y1 - 2016/1/1

N2 - 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.

AB - 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.

KW - Analytics

KW - High-Throughput High-Content Screening

KW - Pipeline

KW - Visualization

UR - https://corescholar.libraries.wright.edu/cse/469

M3 - Article

JO - Default journal

JF - Default journal

ER -

HPC Enabled Data Analytics for High-Throughput High-Content Cellular Analysis

Abstract

Keywords

Disciplines

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