mCUDA-MEME 3.0.16 – Motif Discovery software based on MEME

mCUDA-MEME 3.0.16

:: DESCRIPTION

mCUDA-MEME is a further extension of CUDA-MEME based on MEME algorithm for mutliple GPUs using a hybrid combination of CUDA, MPI and OpenMP.

::DEVELOPER

Liu, Yongchao

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • CUDA toolkits and SDK 2.0 or higher.

:: DOWNLOAD

   CUDA-MEME / mCUDA-MEME

:: MORE INFORMATION

Citation:

Yongchao Liu, Bertil Schmidt, Weiguo Liu, Douglas L. Maskell:
CUDA-MEME: accelerating motif discovery in biological sequences using CUDA-enabled graphics processing units“.
Pattern Recognition Letters, 2010, 31(14): 2170 – 2177

Yongchao Liu, Bertil Schmidt, Douglas L. Maskell:
An ultrafast scalable many-core motif discovery algorithm for multiple GPUs“.
10th IEEE International Workshop on High Performance Computational Biology (HiCOMB 2011), 2011, 428-434

MEME-LaB – Motif analysis in Clusters

MEME-LaB

:: DESCRIPTION

MEME-LaB (MEME Launcher and Browser) provides an interface to run MEME on a range of gene clusters and browse the resulting motifs

::DEVELOPER

Warwick Systems Biology Centre

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Bioinformatics. 2013 Jul 1;29(13):1696-7. doi: 10.1093/bioinformatics/btt248. Epub 2013 May 16.
MEME-LaB: motif analysis in clusters.
Brown P, Baxter L, Hickman R, Beynon J, Moore JD, Ott S.

MEME 5.0.5 – Discovering Motifs within the Sequences

MEME 5.0.5

:: DESCRIPTION

MEME (Multiple Em for Motiv Elicitation) is a tool for discovering motifs in a group of related DNA or protein sequences.A motif is a sequence pattern that occurs repeatedly in a group of related protein or DNA sequences. MEME represents motifs as position-dependent letter-probability matrices which describe the probability of each possible letter at each position in the pattern. Individual MEME motifs do not contain gaps. Patterns with variable-length gaps are split by MEME into two or more separate motifs.MEME takes as input a group of DNA or protein sequences and outputs as many motifs as requested. MEME uses statistical modeling techniques to automatically choose the best width, number of occurrences, and description for each motif.

MCAST searches sequences for clusters of matches to one or more nucleotide motifs

::DEVELOPER

MEME Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

  MEME

:: MORE INFORMATION

Citation

MCAST: Scanning for cis-regulatory motif clusters.
Grant CE, Johnson J, Bailey TL, Noble WS.
Bioinformatics. 2015 Dec 24. pii: btv750

The MEME Suite.
Bailey TL, Johnson J, Grant CE, Noble WS.
Nucleic Acids Res. 2015 May 7. pii: gkv416.

Timothy L. Bailey, Mikael Bodén, Fabian A. Buske, Martin Frith, Charles E. Grant, Luca Clementi, Jingyuan Ren, Wilfred W. Li, William S. Noble,
MEME SUITE: tools for motif discovery and searching“,
Nucleic Acids Research, 37:W202-W208, 2009

MEMERIS 1.0 – MEME in Rna’s Including Secondary Structures

MEMERIS 1.0

:: DESCRIPTION

MEMERIS (Muptiple Em for Motif Elucidation in Rna’s Including Secondary Structures) integrates information about RNA secondary structures into the motif search to guide the search towards single-stranded regions.

::DEVELOPER

Chair for Bioinformatics Freiburg

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 MEMERIS

:: MORE INFORMATION

Citation

Hiller M, Pudimat R, Busch A, and Backofen R.
Using RNA secondary structures to guide sequence motif finding towards single-stranded regions.
Nucleic Acids Res. 2006