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http://owlsim.org

Software package that provides the ability to do a number of standard semantic similarity methods and includes novel methods for combining these with dynamic selection of anonymous grouping classes. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: OwlSim (RRID:SCR_006819) Copy   

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http://www.seqexpress.com/

A comprehensive analysis and visualization software package for gene expression experiments that provides: a number of clustering and analysis techniques; integrated gene expression and analysis result visualizations, integration with the Gene Expression Omnibus; and an optional data sharing architecture. GO is used to assign functional enrichment scores to clusters, using a combination of specially developed techniques and general statistical methods. These results can be explored using the in built ontology browsing tool or through the generated web pages. SeqExpress also supports numerous data transformation, projection, visualization, file export/import, searching, integration (with R), and clustering options.

Proper citation: SeqExpress (RRID:SCR_007075) Copy   

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http://doa.nubic.northwestern.edu/pages/search.php

Project portal for a collaborative database aiming to provide a comprehensive annotation to human genome.It uses the computable, controlled vocabulary of Disease Ontology (DO) and NCBI Gene Reference Into Function (GeneRIF).

Proper citation: DOAF (RRID:SCR_015666) Copy   

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https://syngoportal.org/

Evidence based, expert curated knowledge base for synapse. Universal reference for synapse research and online analysis platform for interpretation of omics data. Interactive knowledge base that accumulates available research about synapse biology using Gene Ontology annotations to novel ontology terms.

Proper citation: SynGO (RRID:SCR_017330) Copy   

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http://www.evidenceontology.org

A controlled vocabulary that describes types of scientific evidence within the realm of biological research that can arise from laboratory experiments, computational methods, manual literature curation, and other means. Researchers can use these types of evidence to support assertions about research subjects that result from scientific research, such as scientific conclusions, gene annotations, or other statements of fact. ECO comprises two high-level classes, evidence and assertion method, where evidence is defined as a type of information that is used to support an assertion, and assertion method is defined as a means by which a statement is made about an entity. Together evidence and assertion method can be combined to describe both the support for an assertion and whether that assertion was made by a human being or a computer. However, ECO can not be used to make the assertion itself; for that, one would use another ontology, free text description, or other means. ECO was originally created around the year 2000 to support gene product annotation by the Gene Ontology. Today ECO is used by many groups concerned with provenance in scientific research. ECO is used in AmiGO 2

Proper citation: ECO (RRID:SCR_002477) Copy   

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http://code.google.com/p/behavior-ontology

An ontology consisting of two main components, an ontology of behavioral processes and an ontology of behavioral phenotypes. The behavioral process branch of NBO contains a classification of behavior processes complementing and extending the GO process ontology. The behavior phenotype branch of NBO consists of a classification of both normal and abnormal behavioral characteristics of organisms. The prime application of NBO is to provide the vocabulary that is required to integrate behavior observations within and across species. It is currently being applied by several model organism communities as well as in the description of human behavior-related disease phenotypes. The main ontology is available in both the OBO Flatfile Format and the Web Ontology Language (OWL).

Proper citation: Neurobehavior Ontology (RRID:SCR_006201) Copy   

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http://bc02.iis.sinica.edu.tw/gobu/manual/index.html

Gene Ontology Browsing Utility (GOBU) (GOBU) is a Java-based software program for integrating biological annotation catalogs under an extendable software architecture. Users may interact with the Gene Ontology and user-defined hierarchy data of genes, and then use its plugins to (and not limited to) (1) browse the GO hierarchy with user defined data, (2) browse GO-oriented expression levels in the user data, (3) compute GO enrichment, and/or (4) customize data reporting. A set of classes and utility functions has been established so that a customized program can be made as a plugin or a command-line tool that programmically manipulate the Gene Ontology and specified user data. See the source code repository for examples. Reference Lin WD, Chen YC, Ho JM, Hsiao CD. GOBU: Toward an Integration Interface for Biological Objects. Journal of Information Science and Engineering. 2006 22(1):19-29. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Gene Ontology Browsing Utility (GOBU) (RRID:SCR_005662) Copy   

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http://owlapi.sourceforge.net/

The OWL API is a Java API and reference implementation for creating, manipulating and serializing OWL Ontologies. The latest version of the API is focused towards OWL 2. The OWLAPI underpins ontology browsing and editing tools and platforms such as SWOOP and Protege4. Note that this API, or any other OWL-based API, can be used without an integrated OWL parser if you download a pre-converted OWL file generated from OBO. See OBO Ontologies List for all OBO ontologies converted to OWL (we do not list the full complement of OWL-based APIs here, only those of direct relevance to GO). The OWL API includes the following components: * An API for OWL 2 and an efficient in-memory reference implementation * RDF/XML parser and writer * OWL/XML parser and writer * OWL Functional Syntax parser and writer * Turtle parser and writer * KRSS parser * OBO Flat file format parser * Reasoner interfaces for working with reasoners such as FaCT++, HermiT, Pellet and Racer Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: OWL API (RRID:SCR_005734) Copy   

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https://planttfdb.gao-lab.org/

Comprehensive plant transcription factor database. Interface to allow users to search the database by IDs or free texts, to make sequence similarity search against TFs of all or individual species, and to download TF sequences for local analysis.PlantTFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors

Proper citation: PLANTTFDB (RRID:SCR_003362) Copy   

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https://bioportal.bioontology.org/ontologies/REX?p=classes&conceptid=http%3A%2F%2Fpurl.obolibrary.org%2Fobo%2FREX_0000000

An ontology of physico-chemical processes, i.e. physico-chemical changes occurring in course of time. It includes both microscopic processes (involving molecular entities or subatomic particles) and macroscopic processes. Some biochemical processes from Gene Ontology (GO Biological process) can be described as instances of REX.

Proper citation: Physico-Chemical Process (RRID:SCR_003530) Copy   

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http://eagl.unige.ch/GOCat/

Software tool that uses a machine learning (ML) approach to classify text, based on the Gene Ontology. It relies on a k-Nearest Neighbours algorithm, a simple algorithm which assigns to a new text the categories that are the most prevalent among the k most similar instances contained in the knowledge base. The ML classifier operates in two steps and combines two components. First, a related article search engine retrieves instances (i.e. abstracts) in the knowledge base that are the most similar to the input text (its nearest neighbours); second, a score computer infers the functional profile from the k most similar instances.

Proper citation: GOCat (RRID:SCR_003608) Copy   

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http://www.cmhd.ca/genetrap/

Generate gene trap insertions using mutagenic polyA trap vectors, followed by sequence tagging to develop a library of mutagenized ES cells freely available to the scientific community. This library is searchable by sequence or key word searches including gene name or symbol, chromosome location, or Gene Ontology (GO) terms. In addition,they offer a custom email alert service in which researchers are able to submit search criteria. Researchers will receive automated e-mail notification of matching gene trap clones as they are entered into the library and database. The resource features the use of complementary second and third generation polyA trap vectors developed by the Stanford lab and the laboratory of Professor Yasumasa Ishida of the Nara Institute of Science and Technology (NAIST) in Japan to mutagenize murine embryonic stem (ES) cells. CMHD gene trap clones are distributed by the Canadian Mouse Mutant Repository(CMMR). Information about ordering, services, and pricing can be found on their web site (http://www.cmmr.ca/services/index.html)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: Centre for Modeling Human Disease Gene Trap Resource (RRID:SCR_002785) Copy   

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http://bioportal.bioontology.org/

Open repository of biomedical ontologies that provides access via Web browsers and Web services to ontologies. It supports ontologies in OBO format, OWL, RDF, Rich Release Format (RRF), Protege frames, and LexGrid XML. Functionality includes the ability to browse, search and visualize ontologies as well as to comment on, and create mappings for ontologies. Any registered user can submit an ontology. The NCBO Annotator and NCBO Resource Index can also be accessed via BioPortal. Additional features: * Add Reviews: rate the ontology according to several criteria and describe your experience using the ontology. * Add Mappings: submit point-to-point mappings or upload bulk mappings created with external tools. Notification of new Mappings is RSS-enabled and Mappings can be browsed via BioPortal and accessed via Web services. * NCBO Annotator: Tool that tags free text with ontology terms. NCBO uses the Annotator to generate ontology annotations, creating an ontology index of these resources accessible via the NCBO Resource Index. The Annotator can be accessed through BioPortal or directly as a Web service. The annotation workflow is based on syntactic concept recognition (using the preferred name and synonyms for terms) and on a set of semantic expansion algorithms that leverage the ontology structure (e.g., is_a relations). * NCBO Resource Index: The NCBO Resource Index is a system for ontology based annotation and indexing of biomedical data; the key functionality of this system is to enable users to locate biomedical data linked via ontology terms. A set of annotations is generated automatically, using the NCBO Annotator, and presented in BioPortal. This service uses a concept recognizer (developed by the National Center for Integrative Biomedical Informatics, University of Michigan) to produce a set of annotations and expand them using ontology is_a relations. * Web services: Documentation on all Web services and example code is available at: BioPortal Web services.

Proper citation: BioPortal (RRID:SCR_002713) Copy   

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http://www.gramene.org

Curated, open-source, integrated data resource for comparative functional genomics in crops and model plant species to facilitate the study of cross-species comparisons using information generated from projects supported by public funds. It currently hosts annotated whole genomes in over two dozen plant species and partial assemblies for almost a dozen wild rice species in the Ensembl browser, genetic and physical maps with genes, ESTs and QTLs locations, genetic diversity data sets, structure-function analysis of proteins, plant pathways databases (BioCyc and Plant Reactome platforms), and descriptions of phenotypic traits and mutations. The web-based displays for phenotypes include the Genes and Quantitative Trait Loci (QTL) modules. Sequence based relationships are displayed in the Genomes module using the genome browser adapted from Ensembl, in the Maps module using the comparative map viewer (CMap) from GMOD, and in the Proteins module displays. BLAST is used to search for similar sequences. Literature supporting all the above data is organized in the Literature database. In addition, Gramene now hosts a variety of web services including a Distributed Annotation Server (DAS), BLAST and a public MySQL database. Twice a year, Gramene releases a major build of the database and makes interim releases to correct errors or to make important updates to software and/or data. Additionally you can access Gramene through an FTP site.

Proper citation: Gramene (RRID:SCR_002829) Copy   

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http://gemdock.life.nctu.edu.tw/3D-Interologs

Database of physical protein-protein interactions across multiple genomes. Based on 3D-domain interolog mapping and a scoring function, protein-protein interactions are inferred by using three-dimensional (3D) structure heterodimers to search the UniProt database. For a query protein, the database utilizes BLAST to identify homologous proteins and the interacting partners from multiple species. Based on the scoring function and structure complexes, it provides the statistic significances, the interacting models (e.g. hydrogen bonds and conserved amino acids), and functional annotations of interacting partners of a query protein. The identification of orthologous proteins of multiple species allows the study of protein-protein evolution, protein functions, and cross-referencing of proteins.

Proper citation: 3D-Interologs (RRID:SCR_003101) Copy   

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http://www.bioperl.org

BioPerl is a community effort to produce Perl code which is useful in biology. This toolkit of perl modules is useful in building bioinformatics solutions in Perl. It is built in an object-oriented manner so that many modules depend on each other to achieve a task. The collection of modules in the bioperl-live repository consist of the core of the functionality of bioperl. Additionally auxiliary modules for creating graphical interfaces (bioperl-gui), persistent storage in RDMBS (bioperl-db), running and parsing the results from hundreds of bioinformatics applications (Run package), software to automate bioinformatic analyses (bioperl-pipeline) are all available as Git modules in our repository. The BioPerl toolkit provides a library of hundreds of routines for processing sequence, annotation, alignment, and sequence analysis reports. It often serves as a bridge between different computational biology applications assisting the user to construct analysis pipelines. This chapter illustrates how BioPerl facilitates tasks such as writing scripts summarizing information from BLAST reports or extracting key annotation details from a GenBank sequence record. BioPerl includes modules written by Sohel Merchant of the GO Consortium for parsing and manipulating OBO ontologies. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: BioPerl (RRID:SCR_002989) Copy   

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http://genecruiser.broadinstitute.org/genecruiser3/

A web service and web application for the annotation of microarray data providing integrated access to genomic information freely available from public data sources.

Proper citation: GeneCruiser (RRID:SCR_003153) Copy   

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http://monarchinitiative.org/

Repository of information about model organisms, in vitro models, genes, pathways, gene expression, protein and genetic interactions, orthology, disease, phenotypes, publications, and authors, and the the ability to navigate multi-scale spatial and temporal phenotypes across in vivo and in vitro model systems in the context of genetic and genomic data, using semantics and statistics. The discovery system provides basic and clinical science researchers, informaticists, and medical professionals with an integrated interface and set of discovery tools to reveal the genetic basis of disease, facilitate hypothesis generation, and identify novel candidate drug targets. The aim for this system is to promote true translational research, in that clinicians can connect with model systems researchers with expertise in related phenotypes, assays, or models. In addition to providing easy-to-use tools to navigate the model-disease data landscape, it also provides services for other resources, and educational outreach regarding the production of structured data for biomedical discovery. Model systems are the cornerstone of biomedical research to investigate biological processes, test gene-based disease hypotheses, and develop and test disease treatments. The vast knowledge about model systems can be better utilized if semantically aggregated and made queryable based on any number of facets, such as phenotypic similarity, network analysis, gene expression and function, and genomics.

Proper citation: Monarch Initiative (RRID:SCR_001373) Copy   

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http://cellfinder.de/about/ontology/

Structured vocabulary to organize cell-associated data and to place these data in clearly defined semantic relations to other biological facts. It describes cell types, their properties and origin and links this information to other existing ontologies like the Cell Ontology (CL), Foundational Model of Anatomy (FMA), Gene Ontology (GO), Mouse Anatomy and others using the top-level ontology BioTop.

Proper citation: CELDA Ontology (RRID:SCR_001601) Copy   

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http://matrixdb.univ-lyon1.fr/

Freely available database focused on interactions established by extracellular proteins and polysaccharides, taking into account the multimeric nature of the extracellular proteins (e.g. collagens, laminins and thrombospondins are multimers). MatrixDB is an active member of the International Molecular Exchange (IMEx) consortium and has adopted the PSI-MI standards for annotating and exchanging interaction data. It includes interaction data extracted from the literature by manual curation, and offers access to relevant data involving extracellular proteins provided by the IMEx partner databases through the PSICQUIC webservice, as well as data from the Human Protein Reference Database. The database reports mammalian protein-protein and protein-carbohydrate interactions involving extracellular molecules. Interactions with lipids and cations are also reported. MatrixDB is focused on mammalian interactions, but aims to integrate interaction datasets of model organisms when available. MatrixDB provides direct links to databases recapitulating mutations in genes encoding extracellular proteins, to UniGene and to the Human Protein Atlas that shows expression and localization of proteins in a large variety of normal human tissues and cells. MatrixDB allows researchers to perform customized queries and to build tissue- and disease-specific interaction networks that can be visualized and analyzed with Cytoscape or Medusa. Statistics (2013): 2283 extracellular matrix interactions including 2095 protein-protein and 169 protein-glycosaminoglycan interactions.

Proper citation: MatrixDB (RRID:SCR_001727) Copy   

•   Source: SciCrunch Registry