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SEBINI specifications

Information


Unique identifier OMICS_18808
Name SEBINI
Alternative name Software Environment for BIological Network Inference
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Windows
Programming languages Java, MATLAB
Computer skills Advanced
Stability No
Maintained No

Versioning


No version available

Maintainer


This tool is not available anymore.

Publications for Software Environment for BIological Network Inference

SEBINI citations

 (3)
library_books

Barcoding of Central European Cryptops centipedes reveals large interspecific distances with ghost lineages and new species records from Germany and Austria (Chilopoda, Scolopendromorpha)

2016
Zookeys
PMCID: 4820090
PMID: 27081331
DOI: 10.3897/zookeys.564.7535

[…] southeastern Germany (ZFMK-DNA-112780049), but these two were collected in a park and a garden.A second distinct group (Fig. : Blue) contains the topotypic specimen of the subspecies Cryptops parisi sebini Verhoeff, 1934. Cryptops parisi sebini was recently synonymised under Cryptops parisi because no morphological differences could be detected (). However, the distinctiveness of the subspecies C […]

library_books

MINER: exploratory analysis of gene interaction networks by machine learning from expression data

2009
BMC Genomics
PMCID: 2788369
PMID: 19958480
DOI: 10.1186/1471-2164-10-S3-S17

[…] .Other interactive methods fall into two categories: network visualisation tools that can incorporate some network inference algorithm, and interactive data mining applications.In the first category, SEBINI [] is designed to be a framework to support testing of network inference algorithms using synthetic and other data sets. However, it has a limited number of inference methods incorporated, and […]

library_books

Coordinated Regulation of Virulence during Systemic Infection of Salmonella enterica Serovar Typhimurium

2009
PLoS Pathog
PMCID: 2639726
PMID: 19229334
DOI: 10.1371/journal.ppat.1000306

[…] g of isogenic derivatives missing the regulator under a variety of growth conditions. The transcriptional profiles provided more than 300,000 data point, necessitating computer analysis. We have used SEBINI (Software Environment for Biological Network Inference; ) to directly compare multiple network algorithms. The network inference algorithm that we have used is the context likelihood of related […]

Citations

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SEBINI institution(s)
Computational Biology and Bioinformatics Group, Pacific Northwest National Laboratory, Richland, WA, USA; Oberlin College, Oberlin, OH, USA; Case Western Reserve University, Cleveland, OH, USA
SEBINI funding source(s)
Supported by the US Department of Energy (DOE) through the Biomolecular Systems Initiative at PNNL, and also through PNNL’s William R. Wiley Environmental Molecular Science Laboratory (EMSL), the EMSL Grand Challenge in Membrane Biology project, via PNNL’s Laboratory Directed Research and Development Program operated by Battelle for the DOE under contract DE-AC05-76RL01830 and the DOE Science Undergraduate Laboratory Internship (SULI) program.

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