Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights

PLoS Computational Biology

Volumn 12, Issue 7, 2016, Pages

  Pasolli, Edoardo ^a   Truong, Duy Tin ^a   Malik, Faizan ^b   Waldron, Levi ^b   Segata, Nicola ^a  

^a UNIVERSITY OF TRENTO   (Italy)

^b CITY UNIVERSITY OF NEW YORK   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER PROGRAMMING; DISEASE CONTROL; LEARNING SYSTEMS;

BIOLOGICAL INSIGHT; CROSS VALIDATION; GENERALISATION; MACHINE-LEARNING; META-ANALYSIS; METAGENOMIC ANALYSIS; METAGENOMICS; MICROBIOME; PREDICTION CAPABILITY; PREDICTION TASKS;

FORECASTING;

ARTICLE; BAYESIAN LEARNING; COLORECTAL CANCER; CONTROLLED STUDY; CROHN DISEASE; DIAGNOSTIC ACCURACY; DISEASE CLASSIFICATION; DYSBIOSIS; FEMALE; HUMAN; INFLAMMATORY BOWEL DISEASE; LIVER CIRRHOSIS; MAJOR CLINICAL STUDY; MALE; METAGENOMICS; OBESITY; PREDICTION; RANDOM FOREST; RECEIVER OPERATING CHARACTERISTIC; SEX DIFFERENCE; STREPTOCOCCUS ANGINOSUS; SUPPORT VECTOR MACHINE; VALIDATION PROCESS; BIOLOGY; COLORECTAL TUMOR; GENETICS; INTESTINE FLORA; MACHINE LEARNING; METAGENOME; PROCEDURES; SOFTWARE;

COLORECTAL NEOPLASMS; COMPUTATIONAL BIOLOGY; GASTROINTESTINAL MICROBIOME; HUMANS; INFLAMMATORY BOWEL DISEASES; MACHINE LEARNING; METAGENOME; METAGENOMICS; OBESITY; SOFTWARE;

EID: 84979971115     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1004977     Document Type: Article

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