The athlete microbiome project: integrating deep learning to reveal microbial associations of physical fitness.
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| Title: | The athlete microbiome project: integrating deep learning to reveal microbial associations of physical fitness. |
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| Authors: | Lewis GS; Department of Biological Sciences, University of Illinois at Chicago, Chicago, Illinois, United States., Adejumo S; Department of Biological Sciences, University of Illinois at Chicago, Chicago, Illinois, United States., Reczek S; Department of Biological Sciences, University of Illinois at Chicago, Chicago, Illinois, United States., Malas J; Department of Biological Sciences, University of Illinois at Chicago, Chicago, Illinois, United States., Ramanauskas K; Department of Biological Sciences, University of Illinois at Chicago, Chicago, Illinois, United States., Walker JF; Department of Biological Sciences, University of Illinois at Chicago, Chicago, Illinois, United States., Cook MD; Department of Kinesiology, North Carolina Agriculture and Technical State University, Greensboro, North Carolina, United States., Horswill CA; Department of Kinesiology and Nutrition, University of Illinois at Chicago, Chicago, Illinois, United States., Hampton-Marcell J; Department of Biological Sciences, University of Illinois at Chicago, Chicago, Illinois, United States. |
| Source: | Physiological genomics [Physiol Genomics] 2026 Apr 01; Vol. 58 (4), pp. 199-211. Date of Electronic Publication: 2026 Mar 28. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: American Physiological Society Country of Publication: United States NLM ID: 9815683 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1531-2267 (Electronic) Linking ISSN: 10948341 NLM ISO Abbreviation: Physiol Genomics Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1531-2267 |
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| DOI: | 10.1152/physiolgenomics.00278.2025 |
