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Identifying keystone species in microbial communities using deep learning.

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Title: Identifying keystone species in microbial communities using deep learning.
Authors: Wang XW; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA., Sun Z; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA., Jia H; School of Life Sciences, Fudan University, Shanghai, China.; Institute of Precision Medicine-Greater Bay Area (Guangzhou), Fudan University, Guangzhou, China., Michel-Mata S; Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA., Angulo MT; Institute of Mathematics, Universidad Nacional Autónoma de México, Juriquilla, Mexico., Dai L; CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Shenzhen, China.; University of Chinese Academy of Sciences, Beijing, China., He X; Department of Microbiology, The Forsyth Institute, Cambridge, MA, USA.; Department of Oral Medicine, Infection and Immunity, Harvard School of Dental Medicine, Boston, MA, USA., Weiss ST; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA., Liu YY; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. yyl@channing.harvard.edu.; Center for Artificial Intelligence and Modeling, The Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Champaign, IL, USA. yyl@channing.harvard.edu.
Source: Nature ecology & evolution [Nat Ecol Evol] 2024 Jan; Vol. 8 (1), pp. 22-31. Date of Electronic Publication: 2023 Nov 16.
Publication Type: Journal Article
Journal Info: Publisher: Springer Nature Country of Publication: England NLM ID: 101698577 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2397-334X (Electronic) Linking ISSN: 2397334X NLM ISO Abbreviation: Nat Ecol Evol Subsets: MEDLINE
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  Data: <searchLink fieldCode="AU" term="%22Wang+XW%22">Wang XW</searchLink>; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.<br /><searchLink fieldCode="AU" term="%22Sun+Z%22">Sun Z</searchLink>; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.<br /><searchLink fieldCode="AU" term="%22Jia+H%22">Jia H</searchLink>; School of Life Sciences, Fudan University, Shanghai, China.; Institute of Precision Medicine-Greater Bay Area (Guangzhou), Fudan University, Guangzhou, China.<br /><searchLink fieldCode="AU" term="%22Michel-Mata+S%22">Michel-Mata S</searchLink>; Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.<br /><searchLink fieldCode="AU" term="%22Angulo+MT%22">Angulo MT</searchLink>; Institute of Mathematics, Universidad Nacional Autónoma de México, Juriquilla, Mexico.<br /><searchLink fieldCode="AU" term="%22Dai+L%22">Dai L</searchLink>; CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Shenzhen, China.; University of Chinese Academy of Sciences, Beijing, China.<br /><searchLink fieldCode="AU" term="%22He+X%22">He X</searchLink>; Department of Microbiology, The Forsyth Institute, Cambridge, MA, USA.; Department of Oral Medicine, Infection and Immunity, Harvard School of Dental Medicine, Boston, MA, USA.<br /><searchLink fieldCode="AU" term="%22Weiss+ST%22">Weiss ST</searchLink>; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.<br /><searchLink fieldCode="AU" term="%22Liu+YY%22">Liu YY</searchLink>; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. yyl@channing.harvard.edu.; Center for Artificial Intelligence and Modeling, The Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Champaign, IL, USA. yyl@channing.harvard.edu.
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