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BMRF-Net: a software tool for identification of protein interaction subnetworks by a bagging Markov random field-based method.


ABSTRACT:

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Identification of protein interaction subnetworks is an important step to help us understand complex molecular mechanisms in cancer. In this paper, we develop a BMRF-Net package, implemented in Java and C++, to identify protein interaction subnetworks based on a bagging Markov random field (BMRF) framework. By integrating gene expression data and protein-protein interaction data, this software tool can be used to identify biologically meaningful subnetworks. A user friendly graphic user interface is developed as a Cytoscape plugin for the BMRF-Net software to deal with the input/output interface. The detailed structure of the identified networks can be visualized in Cytoscape conveniently. The BMRF-Net package has been applied to breast cancer data to identify significant subnetworks related to breast cancer recurrence.

Availability and implementation

The BMRF-Net package is available at http://sourceforge.net/projects/bmrfcjava/. The package is tested under Ubuntu 12.04 (64-bit), Java 7, glibc 2.15 and Cytoscape 3.1.0.

SUBMITTER: Shi X 

PROVIDER: S-EPMC4495295 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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BMRF-Net: a software tool for identification of protein interaction subnetworks by a bagging Markov random field-based method.

Shi Xu X   Barnes Robert O RO   Chen Li L   Shajahan-Haq Ayesha N AN   Hilakivi-Clarke Leena L   Clarke Robert R   Wang Yue Y   Xuan Jianhua J  

Bioinformatics (Oxford, England) 20150308 14


<h4>Unlabelled</h4>Identification of protein interaction subnetworks is an important step to help us understand complex molecular mechanisms in cancer. In this paper, we develop a BMRF-Net package, implemented in Java and C++, to identify protein interaction subnetworks based on a bagging Markov random field (BMRF) framework. By integrating gene expression data and protein-protein interaction data, this software tool can be used to identify biologically meaningful subnetworks. A user friendly gr  ...[more]

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