KISL: knowledge-injected semi-supervised learning for biological co-expression network modules

The exploration of important biomarkers associated with cancer development is crucial for diagnosing cancer, designing therapeutic interventions, and predicting prognoses. The analysis of gene co-expression provides a systemic perspective on gene networks and can be a valuable tool for mining biomar...

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Veröffentlicht in:	Frontiers in genetics Jg. 14; S. 1151962
Hauptverfasser:	Xiao, Gangyi, Guan, Renchu, Cao, Yangkun, Huang, Zhenyu, Xu, Ying
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland Frontiers Media S.A 02.05.2023
Schlagworte:	biological co-expression network factor analysis feature selection Genetics network modules identification semi-supervised learning algorithm biological co-expression network factor analysis semi-supervised learning algorithm feature selection network modules identification
ISSN:	1664-8021, 1664-8021
Online-Zugang:	Volltext
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