research data . Dataset . 2016

Gene expression prediction using low-rank matrix completion

Arnav Kapur; Kshitij Marwah; Gil Alterovitz;
  • Published: 14 Dec 2016
  • Publisher: figshare Academic Research System
Abstract
Abstract Background An exponential growth of high-throughput biological information and data has occurred in the past decade, supported by technologies, such as microarrays and RNA-Seq. Most data generated using such methods are used to encode large amounts of rich information, and determine diagnostic and prognostic biomarkers. Although data storage costs have reduced, process of capturing data using aforementioned technologies is still expensive. Moreover, the time required for the assay, from sample prep
Subjects
ACM Computing Classification System: ComputingMethodologies_PATTERNRECOGNITION
free text keywords: Genetics, 69999 Biological Sciences not elsewhere classified, 80699 Information Systems not elsewhere classified, 19999 Mathematical Sciences not elsewhere classified, Science Policy, Infectious Diseases, Plant Biology, Computational Biology, 110309 Infectious Diseases
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