Ensemble transcript interaction networks: A case study on Alzheimer's disease

Computer Methods and Programs in Biomedicine

Volumn 108, Issue 1, 2012, Pages 442-450

  Armañanzas, Rubén ^a   Larrañaga, Pedro ^a   Bielza, Concha ^a  

^a UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

Author keywords

Alzheimer's disease; Bayesian network classifiers; High throughput data; Interaction networks

Indexed keywords

ALZHEIMER'S DISEASE; BAYESIAN NETWORK CLASSIFIERS; BIOLOGICAL RELATIONSHIPS; DENTATE GYRUS; ENSEMBLE TECHNIQUES; ENTORHINAL CORTEX; EXPRESSION PROFILE; FEATURE SUBSET SELECTION; HIGH-THROUGHPUT; HIGH-THROUGHPUT DATA; INTERACTION NETWORKS; METABOLIC MECHANISM; NON-PARAMETRIC TEST; PROBABILISTIC DEPENDENCE; STATISTICAL ASSESSMENT; SYSTEMS BIOLOGY; TRANSCRIPT PROFILING;

ARTIFICIAL INTELLIGENCE; BAYESIAN NETWORKS; GENES; NEUROLOGY;

ACTIVE NETWORKS;

ALZHEIMER DISEASE; ARTICLE; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; CENTRAL NERVOUS SYSTEM DISEASE; CIRCADIAN RHYTHM; DENTATE GYRUS; ENTORHINAL CORTEX; GENE EXPRESSION; GENE EXPRESSION PROFILING; GERIATRIC CARE; HIPPOCAMPUS; MOLECULAR MECHANICS; PATHOGENESIS;

ALZHEIMER DISEASE; BAYES THEOREM; FEMALE; HUMANS; RNA, MESSENGER;

EID: 84865724465     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2011.11.011     Document Type: Article

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