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Welcome to miniTUBA
In biomedical research and clinical studies, experimental data are often collected across time over a number of similar trials or experimental units. It is often important to know if an intervention or an adverse event (e.g. a drug treatment or a pathogenic infection) would affect the distribution of data over time, and if so, in what manner. Bayesian networks represent a powerful method for identifying causal or apparently causal patterns in various clinical and biomedical research datasets in the field of medical/clinical inference. Bayesian network analysis supports complex inference modeling, including rational decision making systems, which are useful for causality analysis and automated learning. The purpose of miniTUBA is to provide a generic web version tool to allow clinical and biomedical researchers to perform dynamic Bayesian Analysis using temporal datasets. Users will be able to continuously update their data and refine their results. miniTUBA will offer prediction and intervention suggestions based on an automatic learning process pipeline using all data provided.
miniTUBA currently contains both synthetic data and real biomedical research data. Any user can login using our demonstration account and can use synthetic data to test the functions available in the current system. Feedback is welcome. Thanks.
To cite miniTUBA, please reference the following publication:
Zuoshuang Xiang, Rebecca M. Minter, Xiaoming Bi, Peter Woolf, Yongqun He. miniTUBA: medical inference by network integration of temporal data using Bayesian analysis. Bioinformatics. 2007 Sep 15;23(18):2423-32. PMID: 17644819.
Chen F, Ding X, Ding Y, Xiang Z, Li X, Ghosh D, Schurig GG, Sriranganathan N, Boyle SM, He Y. Proinflammatory caspase-2 mediated macrophage cell death induced by rough attenuated Brucella suis. Infection and Immunity. 2011 Apr 4. [Epub ahead of print] [PMID: 21464087].
He Y, Xiang Z. miniTUBA: a web-based dynamic Bayesian network analysis system and an application in host-pathogen interaction analysis. Bayesian Network, Ahmed Rebai (Ed.), ISBN: 978-953-307-124-4, Sciyo, Available from: http://www.intechopen.com/articles/show/title/minituba-a-web-based-dynamic-bayesian-network-analysis-system-.
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