Motevo 1.03 – Integrated Bayesian Probabilistic Methods

Motevo 1.03

:: DESCRIPTION

MotEvo, a integrated suite of Bayesian probabilistic methods for the prediction of TFBSs and inference of regulatory motifs from multiple alignments of phylogenetically related DNA sequences which incorporates all features just mentioned. In addition, MotEvo incorporates a novel model for detecting unknown functional elements that are under evolutionary constraint, and a new robust model for treating gain and loss of TFBSs along a phylogeny. Rigorous benchmarking tests on ChIP-seq datasets show that MotEvos novel features significantly improve the accuracy of TFBS prediction, motif inference, and enhancer prediction.

::DEVELOPER

van Nimwegen Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / MacOsX

:: DOWNLOAD

Motevo

:: MORE INFORMATION

Citation:

Phil Arnold, Ionas Erb, Mikhail Pachkov, Nacho Molina and Erik van Nimwegen
MotEvo: integrated Bayesian probabilistic methods for inferring regulatory sites and motifs on multiple alignments of DNA sequences
Bioinformatics (2012) 28 (4): 487-494.

inGeno 0.6 – Integrated Genome and Ortholog Viewer

inGeno 0.6

:: DESCRIPTION

inGeno is designed for genome sequence comparisons, which has been proven to be powerful, in particular to prokaryotic genomes of close phylogenetic distances. The original purpose of this software is to user-friendly visualize the corresponding relationships between orthologous genes. Step by step, a series of algorithms are implemented and integrated together, thus enable a noise-reducing process, a locus collinear block recognition and a text-mining step, which are helpful for users to extract biological information precisely.

::DEVELOPER

Department of Bioinformatics, University of Würzburg, Germany

:: SCREENSHOTS

:: REQUIREMENTS

Windows / Mac / Linux
Java

:: DOWNLOAD

inGeno

:: MORE INFORMATION

Citation

inGeno–an integrated genome and ortholog viewer for improved genome to genome comparisons.
Liang C, Dandekar T.
BMC Bioinformatics. 2006 Oct 20;7:461.

iFBA 1.0 – Integrated Flux Balance Analysis Model of Escherichia coli

iFBA 1.0

:: DESCRIPTION

iFBA (Integrated Flux Balance Analysis Model of Escherichia coli) includes several MATLAB scripts that simulate E. coli central metabolism and the effects of single gene deletions on metabolism using 3 approaches — iFBA, rFBA, and ODE. The project also includes several MATLAB scripts that simulate biochemical networks using 1) integrated flux balance analysis (iFBA) — a combined FBA, boolean regulatory, and ODE approach; 2) regulatory flux balance analysis (rFBA); and 3) ordinary differential equations (ODE). Additionally, the project includes several MATLAB and php scripts for visualizing metabolic simulations.

::DEVELOPER

Covert Systems Biology Lab

:: SCREENSHOTS

:: REQUIREMENTS

Windows / MacOsX / Linux
MATLAB

:: DOWNLOAD

iFBA

:: MORE INFORMATION

Citation:

Covert, M.W., Xiao, N., Chen, T.J., and Karr, J.R. (2008)
Integrating metabolic, transcriptional regulatory and signal transduction models in Escherichia coli
Bioinformatics. 24(18): 2044-2050.