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Learning representations of microbe-metabolite interactions.
Morton, James T; Aksenov, Alexander A; Nothias, Louis Felix; Foulds, James R; Quinn, Robert A; Badri, Michelle H; Swenson, Tami L; Van Goethem, Marc W; Northen, Trent R; Vazquez-Baeza, Yoshiki; Wang, Mingxun; Bokulich, Nicholas A; Watters, Aaron; Song, Se Jin; Bonneau, Richard; Dorrestein, Pieter C; Knight, Rob.
  • Morton JT; Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.
  • Aksenov AA; Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA.
  • Nothias LF; Collaborative Mass Spectrometry Innovaftion Center, University of California, San Diego, La Jolla, CA, USA.
  • Foulds JR; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA.
  • Quinn RA; Collaborative Mass Spectrometry Innovaftion Center, University of California, San Diego, La Jolla, CA, USA.
  • Badri MH; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA.
  • Swenson TL; Department of Information Systems, University of Maryland Baltimore County, Baltimore, MD, USA.
  • Van Goethem MW; Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA.
  • Northen TR; Department of Biology, New York University, New York, NY, USA.
  • Vazquez-Baeza Y; Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
  • Wang M; Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
  • Bokulich NA; Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
  • Watters A; DOE Joint Genome Institute, Walnut Creek, CA, USA.
  • Song SJ; Jacobs School of Engineering, University of California, San Diego, La Jolla, CA, USA.
  • Bonneau R; Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA.
  • Dorrestein PC; Collaborative Mass Spectrometry Innovaftion Center, University of California, San Diego, La Jolla, CA, USA.
  • Knight R; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA.
Nat Methods ; 16(12): 1306-1314, 2019 12.
Article en En | MEDLINE | ID: mdl-31686038
ABSTRACT
Integrating multiomics datasets is critical for microbiome research; however, inferring interactions across omics datasets has multiple statistical challenges. We solve this problem by using neural networks (https//github.com/biocore/mmvec) to estimate the conditional probability that each molecule is present given the presence of a specific microorganism. We show with known environmental (desert soil biocrust wetting) and clinical (cystic fibrosis lung) examples, our ability to recover microbe-metabolite relationships, and demonstrate how the method can discover relationships between microbially produced metabolites and inflammatory bowel disease.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Bacterias / Microbiota Límite: Animals Idioma: En Año: 2019 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Search on Google

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Bacterias / Microbiota Límite: Animals Idioma: En Año: 2019 Tipo del documento: Article