Exploring the reproducibility of probabilistic causal molecular network models

Pacific Symposium on Biocomputing

Volumn 0, Issue , 2017, Pages 120-131

  Cohain, Ariella ^a   Divaraniya, Aparna A ^a   Zhu, Kuixi ^a   Scarpa, Joseph R ^a   Kasarskis, Andrew ^a   Zhu, Jun ^a   Chang, Rui ^a   Dudley, Joel T ^a   Schadt, Eric E ^a  

^a MOUNT SINAI SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOINFORMATICS; CLUSTERING ALGORITHMS; SAMPLING;

BAYESIA N NETWORKS; BIOMEDICAL SCIENCE; LARGE-SCALES; LIFE SCIENCES RESEARCH; MOLECULAR NETWORK MODELS; NETWORK RECONSTRUCTION; PROBABILISTICS; RECONSTRUCTION ALGORITHMS; REPRODUCIBILITIES; SAMPLE SIZES;

BAYESIAN NETWORKS;

ALGORITHM; BAYES THEOREM; BIOLOGICAL MODEL; BIOLOGY; GENE REGULATORY NETWORK; HUMAN; REPRODUCIBILITY; STATISTICAL MODEL;

ALGORITHMS; BAYES THEOREM; COMPUTATIONAL BIOLOGY; GENE REGULATORY NETWORKS; HUMANS; MODELS, GENETIC; MODELS, STATISTICAL; REPRODUCIBILITY OF RESULTS;

EID: 85024368267     PISSN: 23356928     EISSN: 23356936     Source Type: Journal    
DOI: 10.1142/9789813207813_0013     Document Type: Conference Paper

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