From genome-scale data to models of infectious disease: A Bayesian network-based strategy to drive model development

Mathematical Biosciences

Volumn 270, Issue , 2015, Pages 156-168

  Yin, Weiwei ^a,d   Kissinger, Jessica C ^b   Moreno, Alberto ^c   Galinski, Mary R ^c   Styczynski, Mark P ^a  

^a Georgia Institute of Technology   (United States)

^b UNIVERSITY OF GEORGIA   (United States)

^c EMORY UNIVERSITY SCHOOL OF MEDICINE   (United States)

^d ZHEJIANG UNIVERSITY   (China)

Author keywords

Bayesian network inference; Infectious diseases; Large scale data analysis; Malaria; Model development

Indexed keywords

BAYESIAN NETWORKS; DATA MINING; DIGITAL STORAGE; DISEASES; GENES;

BAYESIAN NETWORK INFERENCE; INFECTIOUS DISEASE; LARGE-SCALE DATA ANALYSIS; MALARIA; MODEL DEVELOPMENT;

DATA REDUCTION;

DATA MINING; DATA SET; GENOME; INFECTIOUS DISEASE; MALARIA; MATHEMATICAL ANALYSIS; MODEL TEST; NUMERICAL MODEL; PATHOGEN;

ARTICLE; BAYESIAN LEARNING; CLUSTER ANALYSIS; DATA ANALYSIS; DATA MINING; DATA PROCESSING; GENOMICS; MALARIA; MATHEMATICAL MODEL; MATHEMATICAL VARIABLE; PSEUDOGENE; ANIMAL; BAYES THEOREM; COMMUNICABLE DISEASE; RHESUS MONKEY; THEORETICAL MODEL;

ANIMALIA;

ANIMALS; BAYES THEOREM; COMMUNICABLE DISEASES; GENOMICS; MACACA MULATTA; MODELS, THEORETICAL;

EID: 84940207451     PISSN: 00255564     EISSN: 18793134     Source Type: Journal    
DOI: 10.1016/j.mbs.2015.06.006     Document Type: Article

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