Machine learning-based differential network analysis: A study of stress-responsive transcriptomes in Arabidopsis

Plant Cell

Volumn 26, Issue 2, 2014, Pages 520-537

  Ma, Chuang ^a   Xin, Mingming ^a   Feldmann, Kenneth A ^a   Wang, Xiangfeng ^a  

^a UNIVERSITY OF ARIZONA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

SODIUM CHLORIDE; TRANSCRIPTOME;

ARABIDOPSIS; ARTICLE; ARTIFICIAL INTELLIGENCE; COMPUTER PROGRAM; DRUG EFFECT; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENE REGULATORY NETWORK; GENETIC ASSOCIATION; GENETIC DATABASE; GENETICS; PHENOTYPE; PHYSIOLOGICAL STRESS; PHYSIOLOGY; PLANT GENE; SIGNAL TRANSDUCTION;

ARABIDOPSIS; ARTIFICIAL INTELLIGENCE; DATABASES, GENETIC; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, PLANT; GENE REGULATORY NETWORKS; GENES, PLANT; GENETIC ASSOCIATION STUDIES; PHENOTYPE; SIGNAL TRANSDUCTION; SODIUM CHLORIDE; SOFTWARE; STRESS, PHYSIOLOGICAL; TRANSCRIPTOME;

EID: 84897076534     PISSN: 10404651     EISSN: 1532298X     Source Type: Journal    
DOI: 10.1105/tpc.113.121913     Document Type: Article

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