Bi-Force v2 – Large-scale Bicluster Editing and its application to Gene Expression data Biclustering

Bi-Force v2

:: DESCRIPTION

Bi-Force is a novel way of modeling the problem as combinatorial optimization problem on graphs: Weighted Bi-Cluster Editing. It is a very flexible model that can handle arbitrary kinds of multi-condition data sets (not limited to gene expression).

::DEVELOPER

Baumbach lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / Windows
Java

:: DOWNLOAD

Bi-Force

:: MORE INFORMATION

Citation

Bi-Force: large-scale bicluster editing and its application to gene expression data biclustering.
Sun P, Speicher NK, Röttger R, Guo J, Baumbach J.
Nucleic Acids Res. 2014 May;42(9):e78. doi: 10.1093/nar/gku201.

RAP – Association Analysis Approach to Biclustering

RAP

:: DESCRIPTION

RAP (Range-support Association Pattern) is an novel approach based on association pattern analysis for discovering constant-row biclusters in gene expression data. Contrary to traditional association pattern discovery approaches, RAP works with real valued data sets without discritizing them. RAP discovers small highly coherent biclusters as opposed to large blocks discovered by traditional biclustering approaches.

::DEVELOPER

Data mining for biomedical informatics at the UMN

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
C++ Compiler

:: DOWNLOAD

RAP

:: MORE INFORMATION

Bimax – Systematic Comparison and Evaluation of Biclustering Methods for Gene Expression Data

Bimax

:: DESCRIPTION

Bimax is asystematic comparison and evaluation of biclustering methods for gene expression data.

::DEVELOPER

the Systems Optimization Group, Institut TIK, ETH Zürich

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

Bimax

:: MORE INFORMATION

Citation

A. Prelic, S. Bleuler, P. Zimmermann, A. Wille, P. Bühlmann, W. Gruissem, L. Hennig, L. Thiele, and E. Zitzler.
A Systematic Comparison and Evaluation of Biclustering Methods for Gene Expression Data.
Bioinformatics, 22(9):1122–1129, 2006.

BicAT 2.22 – Biclustering Analysis Toolbox

BicAT 2.22

:: DESCRIPTION

BicAT is a graphical user interface software for the analysis of gene expression data. It provides five biclustering and two standard clustering algorithms.

::DEVELOPER

the Systems Optimization Group, Institut TIK, ETH Zürich

:: SCREENSHOTS

:: REQUIREMENTS

Linux / Windows / MacOsX
Java

:: DOWNLOAD

BicAT

:: MORE INFORMATION

Citation

Barkow, S., Bleuler, S., Prelic, A., Zimmermann, P., and E. Zitzler.
BicAT: a biclustering analysis toolbox,
Bioinformatics, 2006 22(10):1282-1283