A systematic machine learning and data type comparison yields metagenomic predictors of infant age, sex, breastfeeding, antibiotic usage, country of origin, and delivery type.
Saved in:
| Title: | A systematic machine learning and data type comparison yields metagenomic predictors of infant age, sex, breastfeeding, antibiotic usage, country of origin, and delivery type. |
|---|---|
| Authors: | Le Goallec, Alan1,2 (AUTHOR), Tierney, Braden T.1,3,4,5 (AUTHOR), Luber, Jacob M.1 (AUTHOR), Cofer, Evan M.6 (AUTHOR), Kostic, Aleksandar D.3,4,5 (AUTHOR) aleksandar.kostic@joslin.harvard.edu, Patel, Chirag J.1 (AUTHOR) aleksandar.kostic@joslin.harvard.edu |
| Source: | PLoS Computational Biology. 5/11/2020, Vol. 16 Issue 5, p1-21. 21p. 1 Diagram, 1 Chart, 3 Graphs. |
| Database: | Academic Search Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| ISSN: | 1553734X |
|---|---|
| DOI: | 10.1371/journal.pcbi.1007895 |
