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Molecular Signature identification using Biclustering

Bioconductor version: Release (3.19)

This package is a implementation of biclustering ensemble method MoSBi (Molecular signature Identification from Biclustering). MoSBi provides standardized interfaces for biclustering results and can combine their results with a multi-algorithm ensemble approach to compute robust ensemble biclusters on molecular omics data. This is done by computing similarity networks of biclusters and filtering for overlaps using a custom error model. After that, the louvain modularity it used to extract bicluster communities from the similarity network, which can then be converted to ensemble biclusters. Additionally, MoSBi includes several network visualization methods to give an intuitive and scalable overview of the results. MoSBi comes with several biclustering algorithms, but can be easily extended to new biclustering algorithms.

Author: Tim Daniel Rose [cre, aut], Josch Konstantin Pauling [aut], Nikolai Koehler [aut]

Maintainer: Tim Daniel Rose <tim.rose at>

Citation (from within R, enter citation("mosbi")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

example-workflow HTML R Script
similarity-metrics-evaluation HTML R Script
Reference Manual PDF


biocViews Clustering, Network, Software, StatisticalMethod
Version 1.10.0
In Bioconductor since BioC 3.14 (R-4.1) (2.5 years)
License AGPL-3 + file LICENSE
Depends R (>= 4.1)
Imports Rcpp, BH, xml2, methods, igraph, fabia, RcppParallel, biclust, isa2, QUBIC, akmbiclust, RColorBrewer
System Requirements C++17, GNU make
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Suggests knitr, rmarkdown, BiocGenerics, runibic, BiocStyle, testthat (>= 3.0.0)
Linking To Rcpp, BH, RcppParallel
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Source Package mosbi_1.10.0.tar.gz
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macOS Binary (x86_64) mosbi_1.10.0.tgz
macOS Binary (arm64) mosbi_1.10.0.tgz
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