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http://www.geneontology.org/

Computable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.

Proper citation: Gene Ontology (RRID:SCR_002811) Copy   

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http://geneontology.org/docs/tools-overview/

Collection of tools developed by GO Consortium and by third parties. Tools are listed by category or alphabetically and continue to be improved and expanded.

Proper citation: Gene Ontology Tools (RRID:SCR_006941) Copy   

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http://wiki.geneontology.org/index.php/GOlr

A public Solr index for the Gene Ontology. This index will replace some of the query functionality for GOOSE as well as become the new backend for AmiGO 2 and other services.

Proper citation: GOlr (RRID:SCR_003939) Copy   

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http://amigo.geneontology.org/

Web tool to search, sort, analyze, visualize and download data of interest. Along with providing details of the ontologies, gene products and annotations, features a BLAST search, Term Enrichment and GO Slimmer tools, the GO Online SQL Environment and a user help guide.Used at the Gene Ontology (GO) website to access the data provided by the GO Consortium. Developed and maintained by the GO Consortium.

Proper citation: AmiGO (RRID:SCR_002143) Copy   

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http://code.google.com/p/owltools/

OWLTools (aka OWL2LS - OWL2 Life Sciences) is a java API for accessing ontologies in either OBO or OWL. OWLTools provides a bio-ontologies friendly wrapper on top of the Manchester OWL API. It provides many features, including: * convenience methods for OBO-like properties such as synonyms, textual definitions, obsoletion, replaced_by * simple graph-like operations over ontologies * visualization using the QuickGO graphs libraries Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: OWLTools (RRID:SCR_005732) Copy   

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http://sequenceontology.org/

A collaborative ontology for the definition of sequence features used in biological sequence annotation. SO was initially developed by the Gene Ontology Consortium. Contributors to SO include the GMOD community, model organism database groups such as WormBase, FlyBase, Mouse Genome Informatics group, and institutes such as the Sanger Institute and the EBI. Input to SO is welcomed from the sequence annotation community. The OBO revision is available here: http://sourceforge.net/p/song/svn/HEAD/tree/ SO includes different kinds of features which can be located on the sequence. Biological features are those which are defined by their disposition to be involved in a biological process. Biomaterial features are those which are intended for use in an experiment such as aptamer and PCR_product. There are also experimental features which are the result of an experiment. SO also provides a rich set of attributes to describe these features such as polycistronic and maternally imprinted. The Sequence Ontologies use the OBO flat file format specification version 1.2, developed by the Gene Ontology Consortium. The ontology is also available in OWL from Open Biomedical Ontologies. This is updated nightly and may be slightly out of sync with the current obo file. An OWL version of the ontology is also available. The resolvable URI for the current version of SO is http://purl.obolibrary.org/obo/so.owl.

Proper citation: SO (RRID:SCR_004374) Copy   

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http://search.cpan.org/~cmungall/go-perl/

go-perl is a set of Perl modules for parsing, manipulating and exporting ontologies and annotations. It includes parsers for the OBO and GO gene association file formats. It has a graph-based object model with methods for graph traversal. For more details, see the documentation included with the modules. go-perl comes bundled with XSL (Extensible Stylesheet Language) transforms (which can also be used independently of Perl, provided you have files in OBO-XML format), as well as scripts that can be used as standalone tools. Installation should be simple, provided you have some experience with Perl and CPAN; see the INSTALL file for details. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: go-perl (RRID:SCR_005730) Copy   

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http://search.cpan.org/~cmungall/go-db-perl/

Software resource that extends the functionality of go-perl (on which it depends) with GO Database access functionality. go-db-perl comes bundled with various scripts and a shell command line interface that can be used as standalone tools. Installation is more involved than for go-perl; you will need a MySQL database plus the requisite DBI and DBD Perl modules. Full installation instructions are included in the download. go-db-perl is in use both to drive AmiGO and internally within Ensembl. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: go-db-perl (RRID:SCR_005721) Copy   

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http://purl.bioontology.org/ontology/GO-EXT

An extension of the Gene Ontology.

Proper citation: Gene Ontology Extension (RRID:SCR_010327) Copy   

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http://oboedit.org/

OBO-Edit is an open source, platform-independent application written in Java for viewing and editing any OBO format ontologies. OBO-Edit is a graph-based tool; its emphasis on the overall graph structure of an ontology provides a friendly interface for biologists, and makes OBO-Edit excellent for the rapid generation of large ontologies focusing on relationships between relatively simple classes. The UI components are cleanly separated from the data model and data adapters, so these can be reused in other applications. The oboedit foward-chaining reasoner can also be used independently (for example, for traversing ontology graphs). OBO-Edit uses the OBO format flat file. See the GO wiki, http://wiki.geneontology.org/index.php/OBO-Edit:_Getting_the_Source_Code, for instructions on downloading the source code. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: OBO-Edit (RRID:SCR_005668) Copy   

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http://www.geneontology.org/GO.refgenome.shtml

The GO Consortium coordinates an effort to maximize and optimize the GO annotation of a large and representative set of key genomes, known as ''reference genomes''. The goal of the Reference Genome Annotation project is to completely annotate twelve reference genomes so that those annotations may be used to effectively seed the automatic annotation efforts of other genomes. With more and more genomes being sequenced, we are in the middle of an explosion of genomic information. The limited resources to manually annotate the growing number of sequenced genomes imply that automatic annotation will be the method of choice for many groups. The Reference Genome project has two primary goals: to increase the depth and breadth of annotations for genes in each of the organisms in the project, and to create data sets and tools that enable other genome annotation efforts to infer GO annotations for homologous genes in their organisms. In addition, the project has several important incidental benefits, such as increasing annotation consistency across genome databases, and providing important improvements to the GO''s logical structure and biological content. All GO annotations from this project are included in the gene association files that each group submits to GO. Annotations can also be viewed using the GO search engine and browser AmiGO. Annotated families can be viewed with the homolog set browser.

Proper citation: RefGenome (RRID:SCR_004263) Copy   

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http://www.alliancegenome.org/

Organization that aims to develop and maintain sustainable genome information resources to promote understanding of the genetic and genomic basis of human biology, health, and disease. The Alliance is composed of FlyBase, Mouse Genome Database (MGD), the Gene Ontology Consortium (GOC), Saccharomyces Genome Database (SGD), Rat Genome Database (RGD), WormBase, and the Zebrafish Information Network (ZFIN).

Proper citation: Alliance of Genome Resources (RRID:SCR_015850) Copy   

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http://bioconductor.org/packages/2.9/bioc/html/RamiGO.html

Software package with an R interface sending requests to AmiGO visualize, retrieving DAG GO trees, parsing GraphViz DOT format files and exporting GML files for Cytoscape. Also uses RCytoscape to interactively display AmiGO trees in Cytoscape.

Proper citation: RamiGO (RRID:SCR_006922) Copy   

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http://sourceforge.net/p/fastsemsim/home/Home/

A package that implements several semantic similarity measures. It is both a library and an end-user application, featuring an intuitive graphical user interface (GUI). It has been implemented with the aim of being fast, expandable, and easy to use. It allows the user to work with the most updated version of GO database and customizable annotation corpora. It provides a set of logically-organized classes that can be easily exploited to both integrate semantic similarity into different analysis pipelines and extend the library with new measures. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: FastSemSim (RRID:SCR_006919) Copy   

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http://autismkb.cbi.pku.edu.cn/

Genetic factors contribute significantly to ASD. AutismKB is an evidence-based knowledgebase of Autism spectrum disorder (ASD) genetics. The current version contains 2193 genes (99 syndromic autism related genes and 2135 non-syndromic autism related genes), 4617 Copy Number Variations (CNVs) and 158 linkage regions associated with ASD by one or more of the following six experimental methods: # Genome-Wide Association Studies (GWAS); # Genome-wide CNV studies; # Linkage analysis; # Low-scale genetic association studies; # Expression profiling; # Other low-scale gene studies. Based on a scoring and ranking system, 99 syndromic autism related genes and 383 non-syndromic autism related genes (434 genes in total) were designated as having high confidence. Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder with a prevalence of 1.0-2.6%. The three core symptoms of ASD are: # impairments in reciprocal social interaction; # communication impairments; # presence of restricted, repetitive and stereotyped patterns of behavior, interests and activities.

Proper citation: AutismKB (RRID:SCR_006937) Copy   

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http://mouseNET.princeton.edu

A functional network for laboratory mouse based on integration of diverse genetic and genomic data. It allows the users to accurately predict novel functional assignments and network components. MouseNET uses a probabilistic Bayesian algorithm to identify genes that are most likely to be in the same pathway/functional neighborhood as your genes of interest. It then displays biological network for the resulting genes as a graph. The nodes in the graph are genes (clicking on each node will bring up SGD page for that gene) and edges are interactions (clicking on each edge will show evidence used to predict this interaction). Most likely, the first results to load on the results page will be a list of significant Gene Ontology terms. This list is calculated for the genes in the biological network created by the mouseNET algorithm. If a gene ontology term appears on this list with a low p-value, it is statistically significantly overrepresented in this biological network. The graph may be explored further. As you move the mouse over genes in the network, interactions involving these genes are highlighted.If you click on any of the highlighted interactions graph, evidence pop-up window will appear. The Evidence pop-up lists all evidence for this interaction, with links to the papers that produced this evidence - clicking these links will bring up the relevant source citation(s) in PubMed.

Proper citation: MouseNET (RRID:SCR_003357) Copy   

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http://pathways.mcdb.ucla.edu/algal/

Tools to search gene lists for functional term enrichment as well as to dynamically visualize proteins onto pathway maps. Additionally, integrated expression data may be used to discover similarly expressed genes based on a starting gene of interest.

Proper citation: Algal Functional Annotation Tool (RRID:SCR_012034) Copy   

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http://gmod.org/wiki/Flash_GViewer

Flash GViewer is a customizable Flash movie that can be easily inserted into a web page to display each chromosome in a genome along with the locations of individual features on the chromosomes. It is intended to provide an overview of the genomic locations of a specific set of features - eg. genes and QTLs associated with a specific phenotype, etc. rather than as a way to view all features on the genome. The features can hyperlink out to a detail page to enable to GViewer to be used as a navigation tool. In addition the bands on the chromosomes can link to defineable URL and new region selection sliders can be used to select a specific chromosome region and then link out to a genome browser for higher resolution information. Genome maps for Rat, Mouse, Human and C. elegans are provided but other genome maps can be easily created. Annotation data can be provided as static text files or produced as XML via server scripts. This tool is not GO-specific, but was built for the purpose of viewing GO annotation data. Platform: Online tool

Proper citation: Flash Gviewer (RRID:SCR_012870) Copy   

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http://www.nabc.go.kr/sgd/

Database for ESTs (Expressed Sequence Tags), consensus sequences, bacterial artificial chromosome (BAC) clones, BES (BAC End Sequences). They have generated 69,545 ESTs from 6 full-length cDNA libraries (Porcine Abdominal Fat, Porcine Fat Cell, Porcine Loin Muscle, Liver and Pituitary gland). They have also identified a total of 182 BAC contigs from chromosome 6. It is very valuable resources to study porcine quantitative trait loci (QTL) mapping and genome study. Users can explore genomic alignment of various data types, including expressed sequence tags (ESTs), consensus sequences, singletons, QTL, Marker, UniGene and BAC clones by several options. To estimate the genomic location of sequence dataset, their data aligned BES (BAC End Sequences) instead of genomic sequence because Pig Genome has low-coverage sequencing data. Sus scrofa Genome Database mainly provide comparative map of four species (pig, cattle, dog and mouse) in chromosome 6.

Proper citation: PiGenome (RRID:SCR_013394) Copy   

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http://bis.zju.edu.cn/pnatdb/

Natural Antisense Transcripts (NATs), a kind of regulatory RNAs, occur prevalently in plant genomes and play significant roles in physiological and/or pathological processes. PlantNATsDB (Plant Natural Antisense Transcripts DataBase) is a platform for annotating and discovering NATs by integrating various data sources involving approximately 2 million NAT pairs in 69 plant species. PlantNATsDB also provides an integrative, interactive and information-rich web graphical interface to display multidimensional data, and facilitate plant research community and the discovery of functional NATs. GO annotation and high-throughput small RNA sequencing data currently available were integrated to investigate the biological function of NATs. A ''''Gene Set Analysis'''' module based on GO annotation was designed to dig out the statistical significantly overrepresented GO categories from the specific NAT network. PlantNATsDB is currently the most comprehensive resource of NATs in the plant kingdom, which can serve as a reference database to investigate the regulatory function of NATs.

Proper citation: PlantNATsDB - Plant Natural Antisense Transcripts DataBase (RRID:SCR_013278) Copy   

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