MilkyBase, a database of human milk composition as a function of maternal-, infant- and measurement conditions

Tünde Pacza, Mayara L. Martins, Maha Rockaya, Katalin Müller, Ayan Chatterjee, Albert-László Barabási, József Baranyi
Scientific Data
Volume 9, Article number: 557 (2022)
September 9, 2022

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.

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