Predicting microbiome compositions from species assemblages through deep learning.
Saved in:
| Title: | Predicting microbiome compositions from species assemblages through deep learning. |
|---|---|
| Authors: | Michel-Mata S; Center for Applied Physics and Advanced Technology, Universidad Nacional Autónoma de México, Juriquilla 76230, México.; Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA., Wang XW; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA., Liu YY; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA., Angulo MT; CONACyT - Institute of Mathematics, Universidad Nacional Autónoma de México, Juriquilla 76230, México. |
| Source: | IMeta [Imeta] 2022 Mar; Vol. 1 (1). Date of Electronic Publication: 2022 Mar 01. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: John Wiley & Sons Australia, Ltd on behalf of iMeta Science Country of Publication: Australia NLM ID: 9918350383706676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2770-596X (Electronic) Linking ISSN: 27705986 NLM ISO Abbreviation: Imeta Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2770-596X |
|---|---|
| DOI: | 10.1002/imt2.3 |
