Identification, analysis, and interpretation of a human serum metabolomics causal network in an observational study

Journal of Biomedical Informatics

Volumn 63, Issue , 2016, Pages 337-343

  Yazdani, Azam ^a   Yazdani, Akram ^a   Samiei, Ahmad ^b   Boerwinkle, Eric ^a  

^a UNIVERSITY OF TEXAS SCHOOL OF PUBLIC HEALTH   (United States)

^b UNIVERSITY OF POTSDAM   (Germany)

Author keywords

Causal Bayesian network; Data integration; Instrumental variables; Metabolomics; module

Indexed keywords

AMINO ACIDS; BIOMOLECULES; BODY FLUIDS; DATA INTEGRATION; DIRECTED GRAPHS; GENES;

CAUSAL RELATIONSHIPS; DIRECTED ACYCLIC GRAPH (DAG); EFFECT MEASUREMENTS; GLYCEROPHOSPHOCHOLINE; INSTRUMENTAL VARIABLES; METABOLOMICS; MODULE; OBSERVATIONAL STUDY;

METABOLITES;

AMINO ACID DERIVATIVE; ARACHIDONOYL GLYCEROPHOSPHOCHOLINE; GLUTARYLCARNITINE; GLYCEROPHOSPHORYLCHOLINE; LEUCINE; N ACETYLALANINE; UNCLASSIFIED DRUG; BIOLOGICAL MARKER;

ADULT; ARTICLE; EFFECT SIZE; GENE LINKAGE DISEQUILIBRIUM; GENETIC ALGORITHM; GENETIC VARIABILITY; GENOME; HUMAN; METABOLITE; METABOLOMICS; MIDDLE AGED; OBSERVATIONAL STUDY; PREDICTION; PRIORITY JOURNAL; SINGLE NUCLEOTIDE POLYMORPHISM; ALGORITHM; CAUSALITY; GENETIC VARIATION;

ALGORITHMS; BIOMARKERS; CAUSALITY; GENETIC VARIATION; GENOME; HUMANS; METABOLOMICS;

EID: 84987904669     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2016.08.017     Document Type: Article

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