BaMM!motif pipeline

BaMM!motif specifications

Information


Unique identifier OMICS_11505
Name BaMM!motif
Alternative names Bayesian Markov Model motif discovery, BaMMmotif2, BaMMmotif
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS
Programming languages C++, Python, R
License GNU General Public License version 3.0
Computer skills Advanced
Version 2
Stability Stable
Requirements GCC, CMake, Boost, zoo, argparse, fdrtool, LSD, grid, gdata
Maintained Yes

Subtools


  • De-novo motif discovery
  • Motif database
  • Motif scan
  • Motif-motif comparison

Download


Versioning


Add your version

Documentation


Maintainer


  • person_outline Johannes Soeding <>

Additional information


http://bammserver.readthedocs.io/en/latest/ The previous version can be found at https://github.com/soedinglab/BaMMmotif

Information


Unique identifier OMICS_11505
Name BaMM!motif
Alternative names Bayesian Markov Model motif discovery, BaMMmotif2, BaMMmotif
Interface Web user interface
Restrictions to use None
Programming languages Javascript, Python
Computer skills Basic
Version 1.1
Stability Stable
Maintained Yes

Subtools


  • De-novo motif discovery
  • Motif database
  • Motif scan
  • Motif-motif comparison

Download


Documentation


Maintainer


  • person_outline Johannes Soeding <>

Additional information


http://bammserver.readthedocs.io/en/latest/ The previous version can be found at https://github.com/soedinglab/BaMMmotif

Publications for Bayesian Markov Model motif discovery

BaMM!motif IN pipelines

 (4)
2014
PMCID: 4820030
PMID: 24531765
DOI: 10.1038/nature12974

[…] distribution of obtained values across all promoters was visualized by histograms. in addition, the frequency of the top 10 most abundant pentamers found in the scanned sequences was shown. de novo motif discovery was performed on a set of 14 bp long sequences spanning the region from −35 bp to −22 bp upstream of tss using meme38 (http://meme.sdsc.edu/) with default parameters. […]

2013
PMCID: 4053989
PMID: 23972280
DOI: 10.1186/gb-2013-14-8-r86

[…] [66] and are accessible through geo series accession number gse48791., detection of motifs enriched in svb-dependent and svb-independent epidermal genes was performed using cistargetx [40]. for de novo motif discovery, genomic sequences of enhancer and negative regions were processed through a c++ program and statistical operations performed within the r software, as described [47]. […]

2012
PMCID: 3430608
PMID: 22952822
DOI: 10.1371/journal.pone.0043956

[…] set and annotation database using publicly available data from cgd, sgd and biogrid, together with transcription factor binding data from all currently published chip-chip experiments, our own tf motif database, lists of modulated genes from both transcriptional profiling experiments, and genetic-association data obtained from sga screens measuring cell growth., for de novo identification […]

2008
PMCID: 2441782
PMID: 18474530
DOI: 10.1093/nar/gkn232

[…] sequences. these sequences were divided in 500 bp regions to create sequences of the same length as the target sequences., to determine the optimal positional weight matrix (pwm) for p53scan, the de novo motif discovery program mdmodule (55) was applied to half of the 500 bp target sequences, 773 in total. sequences were ordered based on the chip/total ratio of the highest probe in the peak. […]

BaMM!motif institution(s)
Quantitative and Computational Biology, Max Planck Institute for Biophysical Chemistry, Gottingen, Germany
BaMM!motif funding source(s)
Supported by the German Federal Ministry of Education and Research (BMBF) within the frameworks of e:Bio [SysCore, project 0316176A]; SPP 1935 (project CR 227/6-1) of the German Research Foundation (DFG); and the International Max Planck Research School for Genome Science (IMPRS-GS).

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