Cell-Type-Specific Predictive Network Yields Novel Insights into Mouse Embryonic Stem Cell Self-Renewal and Cell Fate

PLoS ONE

Volumn 8, Issue 2, 2013, Pages

  Dowell, Karen G ^a,b   Simons, Allen K ^a   Wang, Zack Z ^b,c   Yun, Kyuson ^a,b   Hibbs, Matthew A ^a,b,d  

^a JACKSON LABORATORY   (United States)

^b UNIVERSITY OF MAINE   (United States)

^c JOHNS HOPKINS UNIVERSITY   (United States)

^d TRINITY UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ARTICLE; BAYESIAN NETWORK; CELL DIFFERENTIATION; CELL FATE; CELL LINEAGE; CELL RENEWAL; CELL SPECIFICITY; DATA ANALYSIS; DEVELOPMENTAL STAGE; EMBRYONIC STEM CELL; GENE EXPRESSION; GENETIC DATABASE; HIGH THROUGHPUT SEQUENCING; MACHINE LEARNING; MOLECULAR INTERACTION; PREDICTION; RELIABILITY; STEM CELL RESEARCH; WNT SIGNALING PATHWAY;

ANIMALS; BAYES THEOREM; CELL DIFFERENTIATION; COMPUTATIONAL BIOLOGY; EMBRYONIC STEM CELLS; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, DEVELOPMENTAL; GENE REGULATORY NETWORKS; MICE; OPEN READING FRAMES; PROTEIN INTERACTION MAPS; PROTEOME; REPRODUCIBILITY OF RESULTS;

EID: 84874511634     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0056810     Document Type: Article

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