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MilkyBase, a database of human milk composition as a function of maternal-, infant- and measurement conditions
Title / Series / Name
Scientific Data
Publication Volume
9
Publication Issue
1
Pages
Editors
Keywords
Statistics and Probability
Information Systems
Education
Computer Science Applications
Statistics, Probability and Uncertainty
Library and Information Sciences
Information Systems
Education
Computer Science Applications
Statistics, Probability and Uncertainty
Library and Information Sciences
URI
https://hdl.handle.net/20.500.14018/28182
Abstract
This study describes the development of a database, called MilkyBase, of the biochemical composition of human milk. The data were selected, digitized and curated partly by machine-learning, partly manually from publications. The database can be used to find patterns in the milk composition as a function of maternal-, infant- and measurement conditions and as a platform for users to put their own data in the format shown here. The database is an Excel workbook of linked sheets, making it easy to input data by non-computationally minded nutritionists. The hierarchical organisation of the fields makes sure that statistical inference methods can be programmed to analyse the data. Uncertainty quantification and recording dynamic (time-dependent) compositions offer predictive potentials.
Topic
Publisher
Place of Publication
Type
Journal article
Date
2022-12
Language
ISBN
Identifiers
10.1038/s41597-022-01663-1