MilkyBase, a database of human milk composition as a function of maternal-, infant- and measurement conditions
Year: 2022
Type: data-paper
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.
Source: Scientific Data
Language: English
Topic: Infant Nutrition and Health
Subfield: Nutrition and Dietetics
Field: Nursing
Domain: Health Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $2,090
Award: G1015653809
OpenAlex ID: W4295024114
