Open AccessGECO: gene expression correlation analysis after genetic algorithm-driven deconvolution
Author(s) -
Jamil Najafov,
Ayaz Najafov
Publication year - 2018
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bty623
Subject(s) - pairwise comparison , deconvolution , computational biology , correlation , biology , gene , function (biology) , expression (computer science) , computer science , data mining , algorithm , genetics , artificial intelligence , mathematics , geometry , programming language
Large-scale gene expression analysis is a valuable asset for data-driven hypothesis generation. However, the convoluted nature of large expression datasets often hinders extraction of meaningful biological information.
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