scan-x 1.1 – Find Motifs within any Sequence data set

scan-x 1.1

:: DESCRIPTION

scan-x is a software tool designed to find motifs within any sequence data set. The first large scale scan was performed using all available human, mouse, fly and yeast phosphorylation and acetylation data to perform a scan for undiscovered modification sites.

::DEVELOPER

Schwartz Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

Mol Cell Proteomics. 2009 Feb;8(2):365-79. doi: 10.1074/mcp.M800332-MCP200. Epub 2008 Oct 28.
Predicting protein post-translational modifications using meta-analysis of proteome scale data sets.
Schwartz D, Chou MF, Church GM.

Curr Protoc Bioinformatics. 2011 Dec;Chapter 13:Unit 13.16.. doi: 10.1002/0471250953.bi1316s36.
Using the scan-x Web site to predict protein post-translational modifications.
Chou MF, Schwartz D.

SIOMICS 3.0 – Systematic Identification Of Motifs In ChIP-Seq data

SIOMICS 3.0

:: DESCRIPTION

SIOMICS is a software developed to de novo identify motifs in large sequence datasets such as those from ChIP-seq experiments. The output of the software is the ranked motifs and motif modules (significantly co-occurring motif combinations). The statistical evaluation of the predicted motifs and motif modules is also provided.

::DEVELOPER

Hu Lab – Data Integration and Knowledge Discovery @ UCF

:: SCREENSHOTS

SIOMICS

:: REQUIREMENTS

  • Linux/ Windows
  • Python
  • Tkinter
  • Java

:: DOWNLOAD

 SIOMICS

:: MORE INFORMATION

Citation:

Nucleic Acids Res. 2014 Mar;42(5):e35. doi: 10.1093/nar/gkt1288. Epub 2013 Dec 9.
SIOMICS: a novel approach for systematic identification of motifs in ChIP-seq data.
Ding J, Hu H, Li X.

MultiMotif – Finding Statistically Significant labeled Motifs in multi-relational networks

MultiMotif

:: DESCRIPTION

MultiMotif is a tool for finding statistically significant labeled motifs in multi-relational networks with analytically derived p-values. MultiMotif uses a custom version of RI algorithm for counting occurrences of labeled motifs in a graph and implements an analytical model to assess motifs significance without generating random graphs. MultiMotif works on both directed and undirected networks and handle non-induced labeled motifs.

::DEVELOPER

MultiMotif team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • Java

:: DOWNLOAD

MultiMotif

:: MORE INFORMATION

Citation:

Micale G, Pulvirenti A, Ferro A, Giugno R, Shasha D (2019).
Fast methods for finding significant motifs on labelled multi-relational networks.
Journal of Complex Networks, doi:10.1093/comnet/cnz008

FlashMotif – Finding Statistically Significant colored Motifs

FlashMotif

:: DESCRIPTION

FlashMotif is software for finding statistically significant colored motifs with analytically derived p-values. FlashMotif uses the GLabTrie algorithm for counting occurrences of colored motifs in a graph and implements an analytical model to assess motifs significance without generating random graphs. FlashMotif works on both directed and undirected networks and can handle induced and non-induced injective and multiset topological colored motifs with color-topology dependency or independency.

::DEVELOPER

FlashMotif team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • Java

:: DOWNLOAD

FlashMotif

:: MORE INFORMATION

Citation:

Micale G, Giugno R, Ferro A, Mongiovì M, Shasha D, Pulvirenti P (2018).
Fast Analytical Methods for Finding Signicant Colored Graph Motifs.
Data Mining and Knowledge Discovery, 32(2), pp. 504-531, doi:10.1007/s10618-017-0544-8.

WebPSSM – Analyze V3 Loop Coreceptor Motifs

WebPSSM

:: DESCRIPTION

WebPSSM (position-specific scoring matrices ) is a bioinformatic tool for predicting HIV-1 coreceptor usage from amino acid or nucleotide sequences of the third variable loop (V3) of the envelope gene. When a nucleotide sequence is entered, it will be translated to amino acid sequence first. If a nucleotide sequence contains ambiguous bases, it will be translated to all possible amino acid sequences.

::DEVELOPER

Mullins Molecular Retrovirology Lab, University of Washington.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Improved coreceptor usage prediction and genotypic monitoring of R5-to-X4 transition by motif analysis of human immunodeficiency virus type 1 env V3 loop sequences.
Jensen MA, Li FS, van ‘t Wout AB, Nickle DC, Shriner D, He HX, McLaughlin S, Shankarappa R, Margolick JB, Mullins JI.
J Virol. 2003 Dec;77(24):13376-88.

PEnG-motif 1.0.1 – Detect Motifs within large sequence sets

PEnG-motif 1.0.1

:: DESCRIPTION

PEnG-motif is an open-source software package for searching statistically overrepresented motifs (position specific weight matrices, PWMs) in a set of DNA sequences.

::DEVELOPER

Söding Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOs
  • C Compiler
:: DOWNLOAD

PEnG-motif

:: MORE INFORMATION

Dragon PolyA Spotter 1.200 – Predictor of poly(A) motifs within Human Genomic DNA sequences

Dragon PolyA Spotter 1.200

:: DESCRIPTION

The Dragon PolyA Spotter is a tool to predict polyadenylation signals variants in primary human genomic sequences. The application displays predicted polyA signal variants and their positions in each submitted fasta sequence.

::DEVELOPER

Dragon PolyA Spotter Team @ Computational Bioscience Research Center ,  King Abdullah University of Science and Technology

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • C++ Compiler

:: DOWNLOAD

 Dragon PolyA Spotter

:: MORE INFORMATION

Citation

Bioinformatics. 2012 Jan 1;28(1):127-9. Epub 2011 Nov 15.
Dragon PolyA Spotter: predictor of poly(A) motifs within human genomic DNA sequences.
Kalkatawi M, Rangkuti F, Schramm M, Jankovic BR, Kamau A, Chowdhary R, Archer JA, Bajic VB.

Element 2.0 – Identify Over-represented Motifs across groups of Promoters

Element 2.0

:: DESCRIPTION

Element is a web-based tool that identifies over-represented motifs across groups of promoters. Numerous plant genomes are already available online to be run against. If you don’t see your genome of interest, feel free to suggest that we add it.

::DEVELOPER

Mockler Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation:

The DIURNAL project: DIURNAL and circadian expression profiling, model-based pattern matching, and promoter analysis.
Mockler TC, Michael TP, Priest HD, Shen R, Sullivan CM, Givan SA, McEntee C, Kay SA, Chory J.
Cold Spring Harb Symp Quant Biol. 2007;72:353-63. doi: 10.1101/sqb.2007.72.006.