Promoter 2.0 – Transcription Start Sites in Vertebrate DNA

Promoter 2.0

:: DESCRIPTION

Promoter predicts transcription start sites of vertebrate PolII promoters in DNA sequences. It has been developed as an evolution of simulated transcription factors that interact with sequences in promoter regions. It builds on principles that are common to neural networks and genetic algorithms.

::DEVELOPER

DTU Health Tech

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

Promoter

:: MORE INFORMATION

Citation

Promoter 2.0: for the recognition of PolII promoter sequences.
Steen Knudsen
Bioinformatics 15, 356-361, 1999.

PASTAA – Detecting Transcriptions Factors Associated with Functional Categories

PASTAA

:: DESCRIPTION

PASTAA is a software for detecting transcriptions factors associated with functional categories, which utilizes the prediction of binding affinities of a TF to promoters. This binding strength information is compared to the likelihood of membership of the corresponding genes in the functional category under study. Coherence between the two ranked datasets is seen as an indicator of association between a TF and the category. PASTAA is applied primarily to the determination of TFs driving tissue-specific expression.

::DEVELOPER

the Computational Molecular Biology Department at the Max Planck Institute for Molecular Genetics in Berlin, Germany.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C++ compiler

:: DOWNLOAD

 PASTAA

:: MORE INFORMATION

Citation

Helge G. Roider*, Thomas Manke, Sean O’Keeffe, Martin Vingron and Stefan A. Haas
PASTAA: identifying transcription factors associated with sets of co-regulated genes
Bioinformatics (2009) 25 (4): 435-442.

Pscan-ChIP 1.3 – Finding Over-represented Transcription Factor-binding Site Motifs

Pscan-ChIP 1.3

:: DESCRIPTION

PscanChIP is a web server that, starting from a collection of genomic regions derived from a ChIP-Seq experiment, scans them using motif descriptors like JASPAR or TRANSFAC position-specific frequency matrices, or descriptors uploaded by users, and it evaluates both motif enrichment and positional bias within the regions according to different measures and criteria.

::DEVELOPER

Bioinformatics Evolution @nd COmparative geNomics lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 PscanChIP

:: MORE INFORMATION

Citation:

Nucleic Acids Res. 2013 Jul;41(Web Server issue):W535-43. doi: 10.1093/nar/gkt448. Epub 2013 Jun 7.
PscanChIP: Finding over-represented transcription factor-binding site motifs and their correlations in sequences from ChIP-Seq experiments.
Zambelli F1, Pesole G, Pavesi G.

coMotif 1.0 – Identify Transcription Co-regulator Binding Sites in ChIP-seq Data

coMotif 1.0

:: DESCRIPTION

coMotif is a software of three-component mixture framework to model the joint distribution of two motifs as well as the situation where some sequences contain only one or none of the motifs.

::DEVELOPER

coMotif team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 coMotif 

:: MORE INFORMATION

Citation:

Mengyuan Xu, Clarice R. Weinberg, David M. Umbach and Leping Li
coMOTIF: a mixture framework for identifying transcription factor and a coregulator motif in ChIP-seq Data
Bioinformatics (2011) 27 (19): 2625-2632.

Dragon Desert Masker -Transcription Initiation Desert Identification

Dragon Desert Masker

:: DESCRIPTION

Dragon Desert Masker (DDM) is a tool that can with a very high sensitivity demarcate those genomic regions that are unlikely to promote the initiation of transcription.

::DEVELOPER

Computational Bioscience Research Center ,  King Abdullah University of Science and Technology

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 No

:: MORE INFORMATION

Citation

Schaefer U, Kodzius R, Kai C, Kawai J, Carninci P, Hayashizaki Y, Bajic VB.
High sensitivity TSS prediction: estimates of locations where TSS cannot occur.
PLoS One. 2010 Nov 15;5(11):e13934.

TransTermHP 2.09 – Transcription Terminator Predictions

TransTermHP 2.09

:: DESCRIPTION

TransTermHP finds rho-independent transcription terminators in bacterial genomes. Each terminator found by the program is assigned a confidence value that estimates its probability of being a true terminator.

::DEVELOPER

the Center for Bioinformatics and Computational Biology

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 TransTermHP

:: MORE INFORMATION

Citation:

C. Kingsford, K. Ayanbule and S.L. Salzberg.
Rapid, accurate, computational discovery of Rho-independent transcription terminators illuminates their relationship to DNA uptake.
Genome Biology 8:R22 (2007).