| Document Date: 2009-02-17 18:30:20
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City Ann Arbor / / Company Lawrence Livermore National Laboratory / Bayesian Networks / MIT Press / Google / Dynamic Bayesian Networks / Microsoft / Amazon Inc. / Apple Inc. / / Facility Java bridge / / IndustryTerm software license / scientific computing community / network structure learning software / energy matrices / on-demand computing platform / software tools / parallel processing / computing / open source software / software packages / search space / open-source software / parallel processing features / scientific computing / gene networks / usable software / / MarketIndex Python Package / / Organization National Institute of Health / MIT / EDU Department of Chemical Engineering / / Person Shah Peter Woolf / Peter Woolf / Abhik Shah / C. Yoo / V / / Position runner / Editor / controller / / ProgrammingLanguage ANSI C / Numerical python / Java / L / R / C / Python / C++ / / ProvinceOrState Michigan / / PublishedMedium Journal of Machine Learning Research / / Technology Bioinformatics / Java / ANSI C / DNA Chip / cell signaling / Machine Learning / BN algorithms / operating systems / parallel processing / / URL http /
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Journal of Machine Learning Research[removed]162 Submitted 6/08; Revised 10/08; Published 2/09 Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data