期刊
BIOINFORMATICS
卷 33, 期 8, 页码 1250-1252出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btw807
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资金
- MOSAIC European FP7 project [600914]
- COMEX project within the Interuniversity Attraction Poles Programme of the Belgian Science Policy Office
Motivation: A Bayesian Network is a probabilistic graphical model that encodes probabilistic dependencies between a set of random variables. We introduce bnstruct, an open source R package to (i) learn the structure and the parameters of a Bayesian Network from data in the presence of missing values and (ii) perform reasoning and inference on the learned Bayesian Networks. To the best of our knowledge, there is no other open source software that provides methods for all of these tasks, particularly the manipulation of missing data, which is a common situation in practice. Availability and Implementation: The software is implemented in R and C and is available on CRAN under a GPL licence. Contact: francesco.sambo@unipd.it Supplementary information: Supplementary data are available at Bioinformatics online.
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