The use of Bayesian networks for predicting nutrient intake, metabolism, and requirements in silico
Biotin is an essential water-soluble vitamin crucial for maintaining normal body functions. The importance of biotin for human health has been under-appreciated but there is opportunity for future research with a potentially great relevance for human health. BiotinNet is an internet based program that uses Bayesian networks to integrate published data on various aspects of biotin metabolism. Users can provide a combination of values on the levels of biotin related metabolites to obtain the predictions on other metabolites that are not specified. As an inherent feature of Bayesian networks, the uncertainty of the prediction is also quantified and reported to the user. This program enables convenient in silico experiments regarding biotin metabolism, which can help researchers design future experiments while new data can be continuously incorporated.
The functionalities of BiotinNet are available free of charge to all users during the current pilot phase. Please visit the following site - http://stat-biotin.unl.edu/cgi-bin/BiotinNet.cgi
The NGN is currently setting up collaboration with the Holland Computing Center (http://hcc.unl.edu/main/index.php) to develop a platform for NGN investigators and external collaborators for the storage, processing, analysis, and transfer of datasets and other project-related documents.