DiscoverY – Y-contig Identification from Whole Genome Assemblies

DiscoverY

:: DESCRIPTION

DiscoverY is a tool to shortlist Y-specific contigs from an assembly of male whole genome sequencing data, based on exact k-mer matches with a female.

::DEVELOPER

Medvedev Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

DiscoverY

:: MORE INFORMATION

Citation:

Rangavittal, S., Stopa, N., Tomaszkiewicz, M. et al.
DiscoverY: A Classifier for Identifying Y Chromosome Sequences in Male Assemblies
BMC Genomics (2019) 20: 641.

ChromHMM 1.20 – Chromatin State Discovery and Characterization

ChromHMM 1.20

:: DESCRIPTION

ChromHMM is software for learning and characterizing chromatin states. ChromHMM can integrate multiple chromatin datasets such as ChIP-seq data of various histone modifications to discover de novo the major re-occuring combinatorial and spatial patterns of marks.

::DEVELOPER

Kellis Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX/ Windows
  • Java

:: DOWNLOAD

 ChromHMM

:: MORE INFORMATION

Citation

Ernst J and Kellis M.
ChromHMM: automating chromatin-state discovery and characterization.
Nature Methods, 9:215-216, 2012.

MUSA 0.5.6 – DNA Motif Discovery Tool for Simple and Complex Motifs

MUSA 0.5.6

:: DESCRIPTION

MUSA (Motif finding using an UnSupervised Approach) is a new algorithm that can be used either to autonomously find over-represented complex motifs or to estimate search parameters for modern motif finders.

::DEVELOPER

Nuno D. Mendes

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 MUSA

:: MORE INFORMATION

Citation

Mendes ND, Casimiro AC, Santos PM, Sá-Correia I, Oliveira AL, Freitas AT.
MUSA: a parameter free algorithm for the identification of biologically significant motifs.
Bioinformatics. 2006 Dec 15; 22(24): 2996-3002

motif-x 1.2 – Biological Sequence Motif Discovery

motif-x 1.2

:: DESCRIPTION

motif-x (short for motif extractor) is a software tool designed to extract overrepresented patterns from any sequence data set. The algorithm is an iterative strategy which builds successive motifs through comparison to a dynamic statistical background.

::DEVELOPER

Schwartz Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

Curr Protoc Bioinformatics. 2011 Sep;Chapter 13:Unit 13.15-24. doi: 10.1002/0471250953.bi1315s35.
Biological sequence motif discovery using motif-x.
Chou MF, Schwartz D.

MODA – Network Motif Discovery in Biological Networks

MODA

:: DESCRIPTION

MODA is an efficient algorithm for network motif discovery in biological networks.

::DEVELOPER

Laboratory of Systems Biology & Bioinformatics (LBB)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 MODA

:: MORE INFORMATION

Citation

Genes Genet Syst. 2009 Oct;84(5):385-95.
MODA: an efficient algorithm for network motif discovery in biological networks.
Omidi S1, Schreiber F, Masoudi-Nejad A.

Dimont – de-novo Motif Discovery tool

Dimont

:: DESCRIPTION

Dimont is a universal tool for de-novo motif discovery. Dimont has successfully been applied to ChIP-seq, ChIP-exo and protein-binding microarray (PBM) data.

::DEVELOPER

Jstacs Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux/  MacOSX
  • Java

:: DOWNLOAD

 Dimont

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2013 Nov;41(21):e197. doi: 10.1093/nar/gkt831. Epub 2013 Sep 20.
A general approach for discriminative de novo motif discovery from high-throughput data.
Grau J1, Posch S, Grosse I, Keilwagen J.

GRAM 0.6 – Discovery of Gene Modules and Regulatory Networks

GRAM 0.6

:: DESCRIPTION

GRAM (Genetic RegulAtory Modules) identifies modules, collections of genes that share common regulators as well as expression profiles.

::DEVELOPER

the Gifford Laboratory

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux/ Windows/MacOsX
  • Java

:: DOWNLOAD

GRAM

:: MORE INFORMATION

Citation

Nat Biotechnol. 2003 Nov;21(11):1337-42. Epub 2003 Oct 12.
Computational discovery of gene modules and regulatory networks.
Bar-Joseph Z, Gerber GK, Lee TI, Rinaldi NJ, Yoo JY, Robert F, Gordon DB, Fraenkel E, Jaakkola TS, Young RA, Gifford DK.

CNVnator 0.3 – CNV Discovery and Genotyping from Depth of Read Mapping

CNVnator 0.3

:: DESCRIPTION

CNVnator is a tool for Copy number variation (CNV) discovery and genotyping from depth of read mapping.

::DEVELOPER

Gerstein Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 CNVnator

:: MORE INFORMATION

Citation:

CNVnator: an approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing.
Abyzov A, Urban AE, Snyder M, Gerstein M.
Genome Res. 2011 Jun;21(6):974-84. Epub 2011 Feb 7.

GeneNT 1.4.1 – Relevance or Dependency network and Signaling Pathway Discovery

GeneNT 1.4.1

:: DESCRIPTION

GeneNT is a R package to estimate co-expression gene networks

::DEVELOPER

Dongxiao Zhu, Ph.D

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/MacOsX/ Linux
  • R package

:: DOWNLOAD

 GeneNT

:: MORE INFORMATION

Citation:

Network constrained clustering for gene microarray data.
Zhu D, Hero AO, Cheng H, Khanna R, Swaroop A.
Bioinformatics. 2005 Nov 1;21(21):4014-20.