MBiRW specifications


Unique identifier OMICS_11757
Name MBiRW
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
License GNU General Public License version 3.0
Computer skills Advanced
Stability Stable
Source code URL https://codeload.github.com/bioinfomaticsCSU/MBiRW/zip/master
Maintained Yes


No version available


  • person_outline Jianxin Wang

Publication for MBiRW

MBiRW citations


Inferring new indications for approved drugs via random walk on drug disease heterogenous networks

BMC Bioinformatics
PMCID: 5259862
PMID: 28155639
DOI: 10.1186/s12859-016-1336-7

[…] the seven competitive methods, and the results are shown in Fig. . It can be seen that TP-NRWRH obtains the AUC value 0.9546, which is significantly higher than that of other six competitive methods. MBiRW still closely follows our method on Cdataset by 0.9225 AUC value. Interesting, the performance of each method notably rise up on Cdataset compared to PREDICT dataset. In terms of the number of c […]


The extraction of drug disease correlations based on module distance in incomplete human interactome

BMC Syst Biol
PMCID: 5260043
PMID: 28155709
DOI: 10.1186/s12918-016-0364-2

[…] uman interactome [–], which point out the therapeutic importance of modules. In 2016, Luo et al. [] utilized some comprehensive similarity measures and Bi-Random walk (BiRW) to develop a method named MBiRW to identify potential novel indications for a given drug. Yu et al. [] proposed a method based on known protein complexes to infer drug-disease associations in 2015. PREDICT (PREdicting Drug Ind […]

MBiRW institution(s)
School of Information Science and Engineering, Central South University, ChangSha, CHINA; School of Computer and Information Engineering, Henan University, KaiFeng, CHINA; Division of Biomedical Engineering, University of Saskatchewan, SK, Canada; Department of Computer Science, Georgia State University, Atlanta, GA, USA

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