Machine learning models can identify individuals based on a resident oral bacteriophage family.
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| Title: | Machine learning models can identify individuals based on a resident oral bacteriophage family. |
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| Authors: | Mahmoudabadi G; Department of Bioengineering, Stanford University, Stanford, CA, United States., Homyk K; Genentech Inc., San Francisco, CA, United States., Catching AB; Biophysics, National Institute of Allergy and Infectious Diseases, Bethesda, MD, United States., Mahmoudabadi A; WellStar Kennestone Hospital, Marietta, GA, United States., Foley HB; Department of Environmental Health, University of Southern California, Los Angeles, CA, United States., Tadmor AD; Personalized Computational Genomics, Translationale Onkologie an der Universitätsmedizin der Johannes Gutenberg-Universität Mainz, Mainz, Germany., Phillips R; Departments of Biophysics and Biology, California Institute of Technology, Pasadena, CA, United States. |
| Source: | Frontiers in microbiomes [Front Microbiomes] 2024 Sep 03; Vol. 3, pp. 1408203. Date of Electronic Publication: 2024 Sep 03 (Print Publication: 2024). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Media SA Country of Publication: Switzerland NLM ID: 9918540080706676 Publication Model: eCollection Cited Medium: Internet ISSN: 2813-4338 (Electronic) Linking ISSN: 28134338 NLM ISO Abbreviation: Front Microbiomes Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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