Open AccessPhantom: investigating heterogeneous gene sets in time-course data
Author(s) -
Jinghua Gu,
Xuan Wang,
Jinyan Chan,
Nicole Baldwin,
Jacob Turner
Publication year - 2017
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/btx348
Subject(s) - imaging phantom , set (abstract data type) , computer science , data set , data mining , computational biology , artificial intelligence , biology , nuclear medicine , medicine , programming language
Gene set analysis is a powerful tool to study the coordinative change of time-course data. However, most existing methods only model the overall change of a gene set, yet completely overlooked heterogeneous time-dependent changes within sub-sets of genes.
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