sigNetTrainer specifications

Information


Unique identifier OMICS_19847
Name sigNetTrainer
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages C, MATLAB
Computer skills Advanced
Stability Stable
Maintained Yes

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Versioning


No version available

Maintainer


  • person_outline Steffen Klamt

Publication for sigNetTrainer

sigNetTrainer citations

 (2)
library_books

Prediction of disease–gene–drug relationships following a differential network analysis

2016
PMCID: 4816176
PMID: 26775695
DOI: 10.1038/cddis.2015.393

[…] a differential network analysis approach., We also performed a thorough comparison of our method with other methods available for network reconstruction of direct and signed GRNs using CellNOptR and SignetTrainer. In this comparison, we measured the enrichment in experimentally validated interactions in the reconstructed GRNs, as well as the agreement between the GRN models generated by each meth […]

library_books

Network Based Analysis of Nutraceuticals in Human Hepatocellular Carcinomas Reveals Mechanisms of Chemopreventive Action

2015
PMCID: 4505829
PMID: 26225263
DOI: 10.1002/psp4.40

[…] turbations, we subsequently constructed compound-specific signaling networks that combined existing knowledge with HEP3B phosphoproteomic and cytokine-release data employing an adapted version of our SigNetTrainer methodology and a sensitivity analysis for a range of thresholds (see Methods and Supplementary Material).As a result, we visualized how EGCG (Figure ), FIS (Figure ), and ERI (Figure ), […]

sigNetTrainer institution(s)
National Technical University of Athens, Athens, Greece; Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
sigNetTrainer funding source(s)
Supported via European Social Fund (ESF) and Greek National funds through the Operational Program ‘‘Education and Lifelong Learning’’ of the National Strategic Reference Framework (NSRF) - Research Funding Program: ERC; by the German Federal Ministry of Education and Research (‘‘Virtual Liver’’ project (grant 0315744) and ‘‘JAK-Sys’’ project (grant 0316167B)) and by the Federal State of SaxonyAnhalt (Research Center ‘‘Dynamic Systems: Biosystems Engineering’’).

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