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This article is part of the supplement: BioSysBio: Bioinformatics and Systems Biology Conference

Open Access Open Badges Poster presentation

Text-mining, milk proteins and nutraceutical potential – the MilkER project

Stephen Edwards1*, Bonnie Webber1, Carl Holt2 and Lindsay Sawyer1

Author Affiliations

1 Department of Informatics, Edinburgh University, Edinburgh UK

2 Hannah Research Institute, Ayr, KA6 5HL, UK

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BMC Bioinformatics 2005, 6(Suppl 3):P10  doi:10.1186/1471-2105-6-S3-P10

The electronic version of this article is the complete one and can be found online at:

Published:21 September 2005


Milk; Informatics; Database; Text-mining

Poster presentation

The vast amount of literature on milk proteins and genes, and bioactive milk-protein derived peptides cries out for a single informatics resource to focus development of research in the food, health and medical industries. The milkER (Milk Extraction Resource) project aims to provide this. The database contains milk protein and gene sequence information, ligand binding data, bioactive peptide data and protein-protein/disease interaction data for many mammalian species. In addition to a milk literature interface, we aim to include data on the effects of milk composition on growth and health, enzymatic properties of milk proteins, and also proteomic and microarray data.

As well as data collation, milkER also aims to perform text-mining on milk literature allowing discovery of novel functional relationships among milk proteins under physiological and processing conditions, leading to potential health and manufacturing benefits. This will be focused on the interactions of milk proteins physiologically with respect to positive and negative effects in mother, child and consumer. In comparison with labour-based research, conceptual research is more cost-effective and milkER will provide high throughput analysis of the milk literature. The milkER website is online at webcite.