SeSiMCMC 4.36 – Dig For DNA Motifs Gibbs Sampler

SeSiMCMC 4.36

:: DESCRIPTION

The SeSiMCMC (Sequence Similarities by Markov Chain Monte Carlo) algorithm finds DNA motifs of unknown length and complicated structure, such as direct repeats or palindromes with variable spacers in the middle in a set of unaligned DNA sequences. It uses an improved motif length estimator and careful Bayesian analysis to consider site absence in a sequence.

::DEVELOPER

Alexander Favorov

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • WIndows / Linux

:: DOWNLOAD

 SeSiMCMC

:: MORE INFORMATION

Citation:

A Gibbs sampler for identification of symmetrically structured, spaced DNA motifs with improved estimation of the signal length.
Favorov AV, Gelfand MS, Gerasimova AV, Ravcheev DA, Mironov AA, Makeev VJ.
Bioinformatics. 2005 May 15;21(10):2240-5. Epub 2005 Feb 22.

GibbsOS V3 – Robust Identification of Transcriptional Regulatory Networks using a Gibbs Sampler on Outlier Sum Statistic

GibbsOS V3

:: DESCRIPTION

GibbsOS is a Matlab package to infer Transcriptional Regulatory Networks (TRN) by integrating gene expression data with ChIP-on-chip or motif binding information. The main purpose of developing GibbsOS is to identify the true target genes for the given transcription factors under certain condition, which are supported by evidences from both expression profiles and binding information

::DEVELOPER

Computational Bioinformatics & Bio-imaging Laboratory (CBIL)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 GibbsOS

:: MORE INFORMATION

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