Tag: GO

GO2MSIG 20131106 – GO based GSEA Gene Set Generator

GO2MSIG 20131106

:: DESCRIPTION

GO2MSIG generates collections of gene sets in MSigDB format based on the Gene Ontology (GO) project hierarchy and gene association data, for use with the Gene Set Enrichment Analysis (GSEA) implementation available at the Broad Institute. This enables rapid creation of gene set collections for multiple species.

::DEVELOPER

Justin Powell (jacp10 at bioinformatics.org)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / windows/ MacOsX
  • Perl
  • Web Server
  • MySQL

:: DOWNLOAD

 GO2MSIG

:: MORE INFORMATION

MOSAIC 1.1 – GO network Annotation and Partition in Cytoscape

MOSAIC 1.1

:: DESCRIPTION

Mosaic performs network annotation and interactive partitioning driven by the Gene Ontology. The Mosaic algorithm works by first annotating the network with GO terms, followed by partitioning the network into a series of subnetworks based on the biological process annotation of nodes.

::DEVELOPER

the National Resource for Network Biology (NRNB)

:: SCREENSHOTS

MOSAIC

:: REQUIREMENTS

  • Linux / MacOsX  /Windows
  • Java
  • Cytoscape

:: DOWNLOAD

 MOSAIC

:: MORE INFORMATION

Citation:

Bioinformatics. 2012 Jul 15;28(14):1943-4. doi: 10.1093/bioinformatics/bts278. Epub 2012 May 9.
Mosaic: making biological sense of complex networks.
Zhang C1, Hanspers K, Kuchinsky A, Salomonis N, Xu D, Pico AR.

DDF2GO – Translate high throughput DDF Proteomics data into GO CC Annotations

DDF2GO

:: DESCRIPTION

DDF2GO uses high throughput differential detergent fractionation (DDF) proteomics data to assign experimentally based Gene Ontology (GO) cellular component (CC) annotations.

:: DEVELOPER

AgBase

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 DDF2GO

:: MORE INFORMATION

Citation

“A high-throughput experiment-based method to identify subcellular localization,”
Lakshmi R Pillai, et al.

GA2GAQ – GO Annotation Quality(GAQ) Score

GA2GAQ

:: DESCRIPTION

GA2GAQ allows user to quantitatively assess GO annotation of a set of gene products. The GAQ score includes breadth of GO annotation, level of detail for annotation and type of evidence used to make the annotation. The output is a summary of total GAQ scores for each gene product, the number of gene products annotated and the average (mean) GAQ score of the whole set.

:: DEVELOPER

AgBase

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/MacOsX/Linux
  • Perl

:: DOWNLOAD

 GA2GAQ

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2008 Feb;36(2):e12. doi: 10.1093/nar/gkm1167.
Gene Ontology annotation quality analysis in model eukaryotes.
Buza TJ, McCarthy FM, Wang N, Bridges SM, Burgess SC.

GOseq 1.44.0 – Performing Gene Ontology (GO) based tests on RNA-seq data

GOseq 1.44.0

:: DESCRIPTION

GOseq is an R library for performing Gene Ontology (GO) and other category based tests on RNA-seq data, which corrects for selection bias.

::DEVELOPER

WEHI Bioinformatics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 GOseq

:: MORE INFORMATION

Citation

Gene ontology analysis for RNA-seq: accounting for selection bias
Matthew D. Young, Matthew J. Wakefield, Gordon K. Smyth, Alicia Oshlack
Genome Biology 2010, 11:R14 (4 February 2010)

AEGIS – Augmented Exploration of the GO with Interactive Simulations

AEGIS

:: DESCRIPTION

AEGIS is an open-source software with an interactive information-retrieval framework that enables an investigator to navigate through the entire Gene Ontology (GO) graph (with tens of thousands of nodes) and focus on fine-grained details without losing the context.

::DEVELOPER

the Sabatti Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / MacOSX / Linux
  • Python

:: DOWNLOAD

AEGIS

:: MORE INFORMATION

Citation

Zhu J, Zhao Q, Katsevich E, Sabatti C.
Exploratory Gene Ontology Analysis with Interactive Visualization.
Sci Rep. 2019 May 24;9(1):7793. doi: 10.1038/s41598-019-42178-x. PMID: 31127124; PMCID: PMC6534545.

MANGO – Prediction of Protein Function from Manually Annotated proteins based on GO (Gene Ontology)

MANGO

:: DESCRIPTION

MANGO is a server for predicting functional class of a protein. It predict function according to GO categories. The method is developed on protein in UNIPROT database whoes function have been assigned manually according to GO criteria.

::DEVELOPER

Dr. G P S Raghava,

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

Raghava, G. P. S. (2006)
MANGO: prediction of Genome Ontology (GO) class of a protein from its amino acid and dipeptide composition using nearest neighbor approach.
CASP7: 93

annot8r 1.1.1 – BLAST based GO-EC-KEGG Annotation

annot8r 1.1.1

:: DESCRIPTION

annot8r is a tool for the annotation of protein or nucleotide sequences from non model organisms with GO terms, EC numbers and KEGG pathways. The annotation is based on BLAST similarity searches against annotated subsets of EMBL UniProt from which sequences with non-informative entries have been removed. GO, EC and KEGG annotations are saved as flat files and in a relational postgreSQL database to allow for more sophisticated searches within the results.

::DEVELOPER

Ralf Schmid and Mark Blaxter

:: REQUIREMENTS

:: DOWNLOAD

annot8r

:: MORE INFORMATION