A survey of dimension reduction and classification methods for RNA-Seq data on malaria vector

MO Arowolo, MO Adebiyi, C Aremu, AA Adebiyi - Journal of Big Data, 2021 - Springer
Journal of Big Data, 2021Springer
Recently unique spans of genetic data are produced by researchers, there is a trend in
genetic exploration using machine learning integrated analysis and virtual combination of
adaptive data into the solution of classification problems. Detection of ailments and
infections at early stage is of key concern and a huge challenge for researchers in the field
of machine learning classification and bioinformatics. Considerate genes contributing to
diseases are of huge dispute to a lot of researchers. This study reviews various works on …
Abstract
Recently unique spans of genetic data are produced by researchers, there is a trend in genetic exploration using machine learning integrated analysis and virtual combination of adaptive data into the solution of classification problems. Detection of ailments and infections at early stage is of key concern and a huge challenge for researchers in the field of machine learning classification and bioinformatics. Considerate genes contributing to diseases are of huge dispute to a lot of researchers. This study reviews various works on Dimensionality reduction techniques for reducing sets of features that groups data effectively with less computational processing time and classification methods that contributes to the advances of RNA-Sequencing approach.
Springer
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