Catapult – Associating new Genes with Traits, Phenotypes, and Diseases

Catapult

:: DESCRIPTION

Catapult (Combining dATa Across species using Positive-Unlabeled Learning Techniques), is a supervised machine learning method that uses a biased support vector machine where the features are derived from walks in a heterogeneous gene-trait network.

::DEVELOPER

the Marcotte Lab at University of Texas at Austin

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 Catapult

:: MORE INFORMATION

Citation:

Prediction and validation of gene-disease associations using methods inspired by social network analyses.
Singh-Blom UM, Natarajan N, Tewari A, Woods JO, Dhillon IS, Marcotte EM.
PLoS One. 2013 May 1;8(5):e58977. doi: 10.1371/journal.pone.0058977.

DISEASES – Disease-gene Associations Mined from Literature

DISEASES

:: DESCRIPTION

DISEASES is a frequently updated web resource that integrates evidence on disease-gene associations from automatic text mining, manually curated literature, cancer mutation data, and genome-wide association studies.

::DEVELOPER

JensenLab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 DISEASES

:: MORE INFORMATION

Citation

DISEASES: text mining and data integration of disease-gene associations.
Pletscher-Frankild S, Pallejà A, Tsafou K, Binder JX, Jensen LJ.
Methods. 2015 Mar;74:83-9. doi: 10.1016/j.ymeth.2014.11.020.

HOODS – Finding Context-specific Neighborhoods of Proteins, Chemicals and Diseases

HOODS

:: DESCRIPTION

HOODS is a simple algorithm which identifies context-specific neighborhoods of entities from a similarity matrix and a list of entities specifying the context.

::DEVELOPER

Albert Pallejà Caro from the Novo Nordisk Foundation Center for Basic Metabolic Research and Lars Juhl Jensen from the Novo Nordisk Foundation Center for Protein Research.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • Perl

:: DOWNLOAD

 HOODS

:: MORE INFORMATION

Citation

HOODS: finding context-specific neighborhoods of proteins, chemicals and diseases.
Palleja A, Jensen LJ.
PeerJ. 2015 Jun 30;3:e1057. doi: 10.7717/peerj.1057.

PRINCIPLE 1.0 – Associating Genes with Diseases via Network Propagation

PRINCIPLE 1.0

:: DESCRIPTION

PRINCE (PRIoritizatioN and Complex Elucidation) is a method for prioritizing disease associated genes.PRINCIPLE (PRINCe ImPLEmentation) is a client-server implementation of PRINCE

::DEVELOPER

Prof. Roded Sharan

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 PRINCIPLE

:: MORE INFORMATION

Citation

Bioinformatics. 2011 Dec 1;27(23):3325-6. doi: 10.1093/bioinformatics/btr584. Epub 2011 Oct 20.
PRINCIPLE: a tool for associating genes with diseases via network propagation.
Gottlieb A1, Magger O, Berman I, Ruppin E, Sharan R.

MetDisease 1.1.0 – Connecting Metabolites to Diseases via Literature

MetDisease 1.1.0

:: DESCRIPTION

MetDisease is an app for Cytoscape, the bioinformatics network visualization tool. The app is used to annotate a metabolic network with MeSH disease terms, explore related diseases within a network, and link to PubMed references corresponding to any network node and selection of MeSH terms. MeSH terms are controlled vocabulary terms used by the National Library of Medicine to describe the content of the articles indexed in PubMed.

::DEVELOPER

MetDisease team

:: SCREENSHOTS

MetDisease

:: REQUIREMENTS

  • Linux/ Windows/MacOsX
  • Java
  • Cytoscape

:: DOWNLOAD

 MetDisease

:: MORE INFORMATION

Citation

Bioinformatics. 2014 Apr 23. [Epub ahead of print]
MetDisease–connecting metabolites to diseases via literature.
Duren W1, Weymouth T, Hull T, Omenn GS, Athey B, Burant C, Karnovsky A.

MitoDis – Detection of Mitochondrial DNA mutation Involvement in Diseases

MitoDis

:: DESCRIPTION

MitoDis is intended to implement a test to detect mitochondrial DNA mutation involvement.

::DEVELOPER

Fengzhu Sun

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows

:: DOWNLOAD

 MitoDis

:: MORE INFORMATION

Citation

Sun FZ, Cui J, Gavras H, and Schwartz F.
A Novel Class of Tests for the Detection of Mitochondrial DNA Mutation Involvement in Diseases.
Am. J. Hum. Genet. 72 (2003) pp. 1515-1526