Feature selection methods and genomic big data: a systematic review

Khawla Tadist, Said Najah, Nikola S. Nikolov, Fatiha Mrabti, Azeddine Zahi

Research output: Contribution to journalArticlepeer-review

Abstract

In the era of accelerating growth of genomic data, feature-selection techniques are believed to become a game changer that can help substantially reduce the complexity of the data, thus making it easier to analyze and translate it into useful information. It is expected that within the next decade, researchers will head towards analyzing the genomes of all living creatures making genomics the main generator of data. Feature selection techniques are believed to become a game changer that can help substantially reduce the complexity of genomic data, thus making it easier to analyze it and translating it into useful information. With the absence of a thorough investigation of the field, it is almost impossible for researchers to get an idea of how their work relates to existing studies as well as how it contributes to the research community. In this paper, we present a systematic and structured literature review of the feature-selection techniques used in studies related to big genomic data analytics.

Original languageEnglish
Article number79
JournalJournal of Big Data
Volume6
Issue number1
DOIs
Publication statusPublished - 1 Dec 2019

Keywords

  • Feature selection
  • Genomic big data
  • Mapping process
  • Systematic review

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