Integration of metabolomics, lipidomics and clinical data using a machine learning method

BMC Bioinformatics

Volumn 17, Issue , 2016, Pages

  Acharjee, Animesh ^a,b   Ament, Zsuzsanna ^a   West, James A ^a   Stanley, Elizabeth ^a   Griffin, Julian L ^a,b  

^a MEDICAL RESEARCH COUNCIL   (United Kingdom)

^b UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOCHEMISTRY; CHEMICAL ANALYSIS; CYTOLOGY; DISEASES; MASS SPECTROMETRY; METABOLISM; NUTRITION; PHOSPHOLIPIDS; PHYSIOLOGY;

CARBOHYDRATE METABOLISM; CARDIO-VASCULAR DISEASE; DIRECT INFUSION MASS SPECTROMETRIES; INTERMEDIARY METABOLISM; MACHINE LEARNING APPROACHES; MACHINE LEARNING METHODS; NUCLEAR HORMONE RECEPTOR; PEROXISOME PROLIFERATOR-ACTIVATED RECEPTOR;

LEARNING SYSTEMS;

PEROXISOME PROLIFERATOR ACTIVATED RECEPTOR ALPHA; PEROXISOME PROLIFERATOR ACTIVATED RECEPTOR GAMMA;

AGONISTS; ANIMAL; BLOOD ANALYSIS; FACTUAL DATABASE; GENETICS; HUMAN; LIPID METABOLISM; LIVER; MACHINE LEARNING; MALE; METABOLIC SYNDROME X; METABOLISM; METABOLOMICS; OBESITY; PATHOLOGY; RAT; SPRAGUE DAWLEY RAT;

ANIMALS; BLOOD CHEMICAL ANALYSIS; DATABASES, FACTUAL; HUMANS; LIPID METABOLISM; LIVER; MACHINE LEARNING; MALE; METABOLIC SYNDROME X; METABOLOMICS; OBESITY; PPAR ALPHA; PPAR GAMMA; RATS; RATS, SPRAGUE-DAWLEY;

EID: 84997521933     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-016-1292-2     Document Type: Article

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