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
library_books
Bnstruct: an R package for Bayesian Network structure learning in the presence of missing data.
2016 Bioinformatics
DOI: 10.1093/bioinformatics/btw807
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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