Regulatory genes identification within functional genomics experiments for tissue classification into binary classes via machine learning techniques | Zendy

Bushra Wazir | Zendy; Dost Muhammad Khan | Zendy; Umair Khalil | Zendy; Muhammad Hamraz | Zendy; Naz Gul | Zendy; Zardad Khan | Zendy

Open Access

Regulatory genes identification within functional genomics experiments for tissue classification into binary classes via machine learning techniques

Author(s) -

Bushra Wazir,

Dost Muhammad Khan,

Umair Khalil,

Muhammad Hamraz,

Naz Gul,

Zardad Khan

Publication year - 2020

Publication title -

journal of the pakistan medical association

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.242

H-Index - 43

ISSN - 0030-9982

DOI - 10.47391/jpma.201

Subject(s) - random forest , support vector machine , brier score , artificial intelligence , feature selection , machine learning , binary classification , pattern recognition (psychology) , identification (biology) , selection (genetic algorithm) , gene selection , computer science , data mining , medicine , gene , microarray analysis techniques , biology , genetics , botany , gene expression

The aim of this study is to filter out the most informative genes that mainly regulate the target tissue class, increase classification accuracy, reduce the curse of dimensionality, and discard redundant and irrelevant genes.

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