bnstruct specifications

Information


Unique identifier OMICS_14364
Name bnstruct
Alternative name Bayesian Network Structure Learning from Data with Missing Values
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages C, R
License GNU General Public License version 3.0
Computer skills Advanced
Version 1.0.4
Stability Stable
Requirements
methods, R(≥2.10), Matrix, testthat, knitr, graph, Rgraphviz, igraph, bitops, qgraph
Maintained Yes

Versioning


No version available

Documentation


Maintainer


  • person_outline Francesco Sambo

Publication for Bayesian Network Structure Learning from Data with Missing Values

bnstruct citation

library_books

Integration of Distributed Services and Hybrid Models Based on Process Choreography to Predict and Detect Type 2 Diabetes

2017
PMCID: 5795558
PMID: 29286314
DOI: 10.3390/s18010079

[…] …).One interesting model for T2DM detection, which is not based on the aforementioned regressions, is the MOSAIC model [], which is open source and available for research (https://github.com/sambofra/bnstruct (last accessed 15 December 2017)). This model is based on a Bayesian network to impute unknown parameters. The MOSAIC model was built to be applicable in different contexts, and the performan […]

bnstruct institution(s)
IRIDIA-CoDE, Université Libre de Bruxelles, Brussels, Belgium; Department of Information Engineering, University of Padova, Padova, Italy
bnstruct funding source(s)
This work has been partly funded by the MOSAIC European FP7 project (MOdels and Simulation techniques for discovering dIAbetes influence faCtors, Grant No. 600914) and the COMEX project within the Interuniversity Attraction Poles Programme of the Belgian Science Policy Office.

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