KIRMES 0.8 – Kernel-based Identification of Regulatory Modules in Euchromatic Sequences

KIRMES 0.8

:: DESCRIPTION

KIRMES (Kernel-based Identification of Regulatory Modules in Euchromatic Sequences) is a new algorithm that combines the benefits of existing motif finding with the ones of Support Vector Machines (SVMs) to find degenerate motifs in order to improve the modeling of regulatory modules. In experiments on microarray data from Arabidopsis thaliana we were able to show that the newly developed strategy significantly improves the recognition of transcription factor targets.

::DEVELOPER

the Biomedical Informatics Lab of Prof. Dr. Gunnar Rätsch

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux/MacOsX

:: DOWNLOAD

KIRMES

:: MORE INFORMATION

Citation:

KIRMES: kernel-based identification of regulatory modules in euchromatic sequences.
Schultheiss SJ, Busch W, Lohmann JU, Kohlbacher O, Rätsch G.
Bioinformatics. 2009 Aug 15;25(16):2126-33. Epub 2009 Apr 23.

mSD – Regulatory Module Identification

mSD

:: DESCRIPTION

mSD (motif-guided sparse decomposition) identifies gene regulatory modules by integrating gene expression data and DNA sequence motif information. The mSD approach is implemented as a two-step algorithm comprising estimates of (1) transcription factor activity and (2) the strength of the predicted gene regulation event(s).

::DEVELOPER

Computational Bioinformatics & Bio-imaging Laboratory (CBIL)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows
MatLab

:: DOWNLOAD

mSD

:: MORE INFORMATION

Citation:

BMC Bioinformatics. 2011 Mar 22;12:82.
Motif-guided sparse decomposition of gene expression data for regulatory module identification.
Gong T, Xuan J, Chen L, Riggins RB, Li H, Hoffman EP, Clarke R, Wang Y.