A systematic machine learning and data type comparison yields metagenomic predictors of infant age, sex, breastfeeding, antibiotic usage, country of origin, and delivery type.

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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
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  Data: <searchLink fieldCode="JN" term="%22PLoS+Computational+Biology%22">PLoS Computational Biology</searchLink>. 5/11/2020, Vol. 16 Issue 5, p1-21. 21p. 1 Diagram, 1 Chart, 3 Graphs.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=143157859
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        Value: 10.1371/journal.pcbi.1007895
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        Text: English
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              Text: 5/11/2020
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