Sparse and Compositionally Robust Inference of Microbial Ecological Networks

PLoS Computational Biology

Volumn 11, Issue 5, 2015, Pages

  Kurtz, Zachary D ^a   Müller, Christian L ^b,c   Miraldi, Emily R ^a,b,c   Littman, Dan R ^a   Blaser, Martin J ^a   Bonneau, Richard A ^b,c,d  

^a NEW YORK UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b NEW YORK UNIVERSITY   (United States)

^c NEW YORK UNIVERSITY   (United States)

^d Simons Center for Data Analysis   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CHEMICAL DETECTION; INVERSE PROBLEMS; MICROORGANISMS; RNA; STATISTICAL MECHANICS;

AMPLICONS; COVARIANCE ESTIMATION; ECOLOGICAL ASSOCIATIONS; ECOLOGICAL NETWORKS; INVERSE COVARIANCE; MICROBIAL COMMUNITIES; MICROBIAL POPULATIONS; OPERATIONAL TAXONOMIC UNITS; ROBUST INFERENCE; RRNA GENES;

NETWORK TOPOLOGY;

AMPLICON; ARTICLE; CONTROLLED STUDY; DATA ANALYSIS; ECOLOGY; GENE SEQUENCE; MICROBIAL COMMUNITY; MICROBIAL ECOLOGICAL NETWORK; MICROBIOME; NONHUMAN; POPULATION ABUNDANCE; QUALITY CONTROL; SPARSE INVERSE COVARIANCE ESTIMATION FOR ECOLOGICAL ASSOCIATION INFERENCE; STANDARD; STATISTICAL ANALYSIS; ALGORITHM; BIOLOGICAL MODEL; BIOLOGY; BIOTA; GENETICS; HUMAN; INTESTINE FLORA; METAGENOMICS; MICROFLORA; PHYSIOLOGY; PROCEDURES;

MAMMALIA; OTUS;

RNA 16S;

ALGORITHMS; BIOTA; COMPUTATIONAL BIOLOGY; GASTROINTESTINAL MICROBIOME; HUMANS; METAGENOMICS; MICROBIOTA; MODELS, BIOLOGICAL; RNA, RIBOSOMAL, 16S;

EID: 84930608352     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1004226     Document Type: Article

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