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Feature selection methods and genomic big data: a systematic review
Tadist, Khawla; Najah, Said; Nikolov, Nikola S.; Mrabti, Fatiha; Zahi, Azeddine
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
Keyword(s): Systematic review; Mapping process; Genomic big data; Feature selection
Publication Date:
2019
Type: Journal article
Peer-Reviewed: Yes
Language(s): English
Institution: University of Limerick
Citation(s): Journal of Big Data;6,79
Publisher(s): SpringerOpen
First Indexed: 2019-09-22 06:43:33 Last Updated: 2019-09-22 06:43:33