A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Optimizing High Performance Big Data Cancer Workflows
2017
Proceedings of the Practice and Experience in Advanced Research Computing 2017 on Sustainability, Success and Impact - PEARC17
Appropriate optimization of bioinformatics workflows is vital to improve the timely discovery of variants implicated in cancer genomics. Sequenced human brain tumor data was assembled to optimize tool implementations and run various components of RNA sequence (RNA-seq) workflows. The measurable information produced by these tools account for the success rate and overall efficiency of a standardized and simultaneous analysis. We used the National Center for Biotechnology Information) Sequence
doi:10.1145/3093338.3093372
dblp:conf/xsede/Jimenez-RuizGR17
fatcat:lzpwkbqoafaexlj4o5x2rhcv34