A systematic machine learning and data type comparison yields metagenomic predictors of infant age, sex, breastfeeding, antibiotic usage, country of origin, and delivery type is a research paper published in PLoS Computational Biology (2020). On theSindex it has a DataRank of 0. It has been cited 33 times.
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National Institute of Allergy and Infectious Diseases
Grant: R01AI127250
National Institute of Environmental Health Sciences
Grant: R00ES23504
National Institute of Diabetes and Digestive and Kidney Diseases
Grant: DK110919
National Science Foundation
Grant: 1636870
NIDDK NIH HHS
Grant: P30 DK036836
NIDDK NIH HHS
Grant: T32 DK110919
NHGRI NIH HHS
Grant: T32 HG002295
NHGRI NIH HHS
Grant: T32 HG003284
NIEHS NIH HHS
Grant: R21 ES025052
NIEHS NIH HHS
Grant: R00 ES023504
National Institutes of Health
Grant: 2T32HG003284-21
Quantitative and Computational Biology Graduate Program
National Institutes of Health
Grant: 5R01AI127250-04
Big Data Analysis of HIV Risk and Epidemiology in Sub-Saharan Africa
National Institutes of Health
Grant: 4R00ES023504-03
Data-driven identification of environmental factors in cardiovascular disease
National Institutes of Health
Grant: 3T32DK110919-03S1
Harvard Training Program in Bioinformatics Applied to Diabetes, Obesity and Metabolism.
Richard and Susan Smith Family Foundation
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Sustainable Development Goals