CFEA / Cell-Free Epigenome Atlas
BaFF / Bacterial Feature Finder
BrAPI / Breeding Application Programming Interface
Drug ReposER / DRug REPOSitioning Exploration Resource
GOLD / Genomes OnLine database
GIDB / GastroIntestinal cancer knowledge DataBase
Haemopedia RNA-seq
DO / Disease Ontology
Consists of a standardized ontology for human disease. DO provides descriptions of human disease terms, phenotype characteristics and related medical vocabulary disease concepts. It integrates disease and medical vocabularies through extensive cross mapping of its terms to MeSH, ICD, NCI’s thesaurus, SNOMED and OMIM. This platform facilitates gene and allele comparative analysis.
OAE / Ontology of Adverse Events
A biomedical ontology that logically defines and classifies various adverse events occurring after medical interventions. OAE has successfully been applied in several adverse event studies. The OAE ontological framework provides a platform for systematic representation and analysis of adverse events and of the factors (e.g., vaccinee age) important for determining their clinical outcomes.
ATMO / African Traditional Medicine Ontology
An ontology for African Traditional Medicine (ATM), which is the basis for a knowledge management system, controlled by a multi-agent system. The interest of this problem, from the point of view of artificial intelligence and software engineering lies on the issues that arise from integration of the requirements of the different stakeholders in such a system and the diverse nature of concepts to be considered in such an ontology. One of these issues is the need to allow the ontology to evolve as far as experts provide more knowledge and the mechanisms for validation of such knowledge.
ADO / Alzheimer's disease ontology
It is constructed in accordance to the ontology building life cycle. The Protege OWL editor was used as a tool for building ADO in Ontology Web Language format. ADO was developed with the purpose of containing information relevant to four main biological views-preclinical, clinical, etiological, and molecular/cellular mechanisms-and was enriched by adding synonyms and references.
ASDPTO / Autism Spectrum Disorder Phenotype Ontology
It has promise for use in research settings where extensive phenotypic data have been collected, allowing a concept-based approach to identifying behavioral features of importance and for correlating these with genotypic data.
ONTOAD / Bilingual Ontology of Alzheimer's Disease and Related Diseases
A method for building a bilingual domain ontology from textual and termino-ontological resources intended for semantic annotation and information retrieval of textual documents. This method combines two approaches: ontology learning from texts and the reuse of existing terminological resources.
BDO / Bone Dysplasia Ontology
Represents the most comprehensive structured knowledge source for the skeletal dysplasias domain. It provides the means for integrating and annotating clinical and research data, not only at the generic domain knowledge level, but also at the level of individual patient case studies. It enables links between individual cases and publicly available genotype and phenotype resources based on a community-driven curation process that ensures a shared conceptualisation of the domain knowledge and its continuous incremental evolution.
ND / Neurological Disease Ontology
Provides a framework to enable representation of aspects of neurological diseases that are relevant to their treatment and study. ND is a representational tool that addresses the need for unambiguous annotation, storage, and retrieval of data associated with the treatment and study of neurological diseases.
DGA / Disease and Gene Annotations
A collaborative effort aiming to provide a comprehensive and integrative annotation of the human genes in disease network context by integrating computable controlled vocabulary of the Disease Ontology, NCBI Gene Reference Into Function (GeneRIF) and molecular interaction network (MIN). DGA integrates these resources together using semantic mappings to build an integrative set of disease-to-gene and gene-to-gene relationships with excellent coverage based on current knowledge.
NCIT / National Cancer Institute Thesaurus
Gathers more than 100000 terms dealing with biomedical concepts. NCIT provides a controlled vocabulary encompassing the fields of clinical care, public information and topics related to research. This resource displays definitions and linked information related to over 10000 cancers and 8000 single agents and combination therapies. This tool is used by several administrations such as the U.S. Food and Drug Administration (FDA).
UMLS / Unified Medical Language System
A repository of biomedical vocabularies developed by the US National Library of Medicine. Vocabularies integrated in the UMLS Metathesaurus include the NCBI taxonomy, Gene Ontology, the Medical Subject Headings (MeSH), OMIM and the Digital Anatomist Symbolic Knowledge Base.
SNOMED-CT / SNOMED Clinical Terms
A comprehensive, multilingual clinical healthcare terminology. SNOMED-CT contributes to the improvement of patient care by underpinning the development of Electronic Health Records that record clinical information in ways that enable meaning-based retrieval. This provides effective access to information required for decision support and consistent reporting and analysis.
A unique resource that integrates OMIM terms, synonyms and identifiers with MeSH terms, synonyms, definitions, identifiers and hierarchical relationships. MEDIC is both a deep and broad vocabulary, composed of 9700 unique diseases described by more than 67 000 terms (including synonyms). It is freely available to download in various formats from Comparative Toxicogenomics Database (CTD).
BAO-GPCR / GPCR ontology
Facilitates integration and aggregation of GPCR-targeting drugs and demonstrate its application to classify and analyze a large subset of the PubChem database. The GPCR ontology, based on previously reported BioAssay Ontology, depicts available pharmacological, biochemical and physiological profiles of GPCRs and their ligands.
VariO / Variation Ontology
An ontology for standardized, systematic description of effects, consequences and mechanisms of variations. VariO allows unambiguous description of variation effects as well as computerized analyses over databases utilizing the ontology for annotation. VariO is a position specific ontology that can be used to describe effects of variations on DNA, RNA and/or protein level, whatever is appropriate.
HGVS / Human Genome Variation Society Sequence Variant Nomenclature
Recommendations for the description of sequence variants. HGVS-nomenclature is used to report and exchange information regarding variants found in DNA, RNA and protein sequences and serves as an international standard in DNA diagnostics. HGVS-nomenclature is authorised by the Human Genome Variation Society (HGVS), the Human Variome Project (HVP) and the HUman Genome Organization (HUGO). The HGVS recommendations are designed to be stable, meaningful, memorable, and unequivocal.
An ontology to define the RDF namespace, concepts and relationships between concepts to be used for exporting glycomics data into a standardized representation using RDF. The ontology contains classes and predicates necessary for the diverse data types used in glycomics databases, and also reuses concepts from other well-established ontologies. The objective of GlycoRDF is to minimize the development of multiple RDF dialects that complicate the querying and mash-up of the information across several resources.
FROG / FingeRprinting Ontology of Genomic variations
A semantic approach is implemented to label variation data, based on its location, function and interactions. FROG has six levels to describe the variation annotation, namely, chromosome, DNA, RNA, protein, variations and interactions. Each level is a conceptual aggregation of logically connected attributes each of which comprises of various properties for the variant. For example, in chromosome level, one of the attributes is location of variation and which has two properties, allosomes or autosomes. Another attribute is variation kind which has four properties, namely, indel, deletion, insertion, substitution. FROG is a unique method designed for the purpose of labeling the entire variation data generated till date for efficient storage, search and analysis.
GFVO / Genomic Feature and Variation Ontology
Enables the generic representation of genomic feature and variation data. GFVO specifically addresses genomic data as it is regularly shared using the GFF3 (incl. FASTA), GTF, GVF and VCF file formats. GFVO simplifies data integration and enables linking of genomic annotations across datasets through common semantics of genomic types and relations.
HPO / Human Phenotype Ontology
Provides a standardized vocabulary of phenotypic abnormalities encountered in human disease. HPO is developed using the medical literature, Orphanet, DECIPHER, and OMIM. HPO contains approximately 11,000 terms and over 115,000 annotations to hereditary diseases. HPO also provides a large set of HPO annotations to approximately 4000 common diseases. HPO can be used for clinical diagnostics in human genetics (Phenomizer), bioinformatics research on the relationships between human phenotypic abnormalities and cellular and biochemical networks, for mapping between human and model organism phenotypes, and for providing a standardized vocabulary for clinical databases, among many other things.
CELDA / Cell: Expression, Localization, Development, Anatomy
An ontology for the association of primary experimental data and derived knowledge to various types of cells of organisms. CELDA is a structure that can help to categorize cell types based on species, anatomical localization, subcellular structures, developmental stages and origin. It targets cells in vitro as well as in vivo. CELDA can semantically link diverse types of information about cell types. It has been integrated within the research platform CellFinder, where it exemplarily relates cell types from liver and kidney during development on the one hand and anatomical locations in humans on the other, integrating information on all spatial and temporal stages.
OBI / Ontology for Biomedical Investigations
Provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. This ontology supports the consistent annotation of biomedical investigations, regardless of the particular field of study. The ontology represents the design of an investigation, the protocols and instrumentation used, the material used, the data generated and the type analysis performed on it. The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions.
EFO / Experimental Factor Ontology
An application ontology driven by the annotation and query needs of samples in omics datasets. EFO provides an integration framework for ontologies and combines parts of several biological ontologies such as UBERON anatomy, ChEBI chemical compounds, and Cell Ontology. The relationship between ontology descriptions of rare and common diseases and their phenotypes can offer insights into shared biological mechanisms and potential drug targets. The scope of EFO is to support the annotation, analysis and visualization of several domain specific ontologies.
ICEPO / Ion Channel ElectroPhysiology Ontology
An ontological framework to annotate the electrophysiological class of ion channels. ICEPO is the translation of quantitative assertions extracted through text mining to a formal representation that may help in constructing ontology for ion channel events. The ICEPO ontology is an outcome based on three approaches: i) anecdotal and domain knowledge of the authors, ii) relations extracted from the biomedical text both abstracts and full-text articles, and iii) integration of vocabularies from other existing ontologies. ICEPO focuses on the description of the biophysical properties of voltage-gated ion channels. Ion channels are classified according to either the type of ions for which they are permeable, their three-dimensional structure or the type of stimulus that triggers their activation gating.
ENVO / Environment Ontology
A resource for the semantically controlled description of environmental entities. ENVO bridges multiple domains including biomedicine, natural and anthropogenic ecology, omics and socioeconomic development. It provides a vocabulary to characterise sequenced environmental samples, together with an ontological structure to facilitate search, advanced querying, and inference in support of the aims of the genomics standards consortium. ENVO includes some 2159 classes primarily representing biomes, geographic features, and environmental materials, along with 18,791 axioms.
An ontology of prokaryotic phenotypes and metabolic characters. MicrO was built to support the ongoing development of a natural language processing algorithm, Microbial Phenomics Information Extractor. MicrO consists of ~2550 classes derived from text contained in the taxonomic descriptions of diverse prokaryotic taxa that span the archaeal and bacterial domains of life. The largest categories of classes in the ontology include assays (enzymatic, metabolic, and phenotypic assays), microbiological culture media and media ingredients, and prokaryotic qualities.
MGED Ontology / Microarray Gene Expression Database Ontology
Provides terms for annotating all aspects of a microarray experiment from the design of the experiment and array layout, through to the preparation of the biological sample and the protocols used to hybridize the RNA and analyze the data. The MGED Ontology does not attempt to incorporate terms from existing ontologies, e.g. those that deal with anatomical parts or developmental stages terms, but provides a framework to reference terms in other ontologies and therefore facilitates the use of ontologies in microarray data annotation.
CogPO / Cognitive Paradigm Ontology
Represents certain characteristics of the cognitive paradigms used in the fMRI and PET literature. CogPO is compliant with the Basic Formal Ontology (BFO), and harmonizes where possible with larger ontologies such as RadLex, NeuroLex, or the Ontology of Biomedical Investigations (OBI). It aims to develop, evaluate, and distribute a domain ontology of cognitive paradigms for application and use in the functional neuroimaging community.
CiTO / Citation Typing Ontology
Describes the nature of reference citations in scientific research articles and other scholarly works, both to other such publications and also to Web information resources, and for publishing these descriptions on the Semantic Web. CiTO has been designed with the requirements of biomedical researchers in mind. It enables the citations within a citing work to be recorded and published in machine-readable form as RDF (resource description framework).
Allows scientists and clinicians to use, for the first time, identical terms with the same meaning in immunogenetics. IMGT-ONTOLOGY provides a semantic repository that will improve interoperability between specialist and generalist databases. It provides a semantic classification and standardization of the knowledge in the immunogenetics field used to identify the sequences, to describe their detailed composition, to classify Ig and TcR genes, and to define in which experimental, biological or medical context the sequences have been obtained.
SO / Sequence Ontology
Regroups a set of terms and relationships used to describe the features and attributes of biological sequence. SO includes different kinds of features which can be located on the sequence. It maintains and updates the specification and provides the underlying ontological structure. The terminology was used to annotate the human reference genome with a set of variants from both COSMIC and dbSNP.
IDOBRU / Brucellosis Ontology
Covers and crosses the biomedical domains of clinical care, public health and biomedical research in the specific brucellosis field. Brucellosis Ontology (IDOBRU) is an extension ontology of the Infectious Disease Ontology (IDO) with a focus on brucellosis, a zoonotic infectious disease caused by Brucella spp. It can be used as a brucellosis knowledgebase and is applicable for brucellosis data exchange, data integration, and automated reasoning.
Represents body parts, organs and tissues in a variety of animal species, with a focus on vertebrates. Uberon is an integrated cross-species ontology covering anatomical structures in animals. It has been constructed to integrate seamlessly with other ontologies, such as the OBO Cell Ontology, the Gene Ontology, Trait and Phenotype ontologies, as well as other anatomical ontologies. It includes comprehensive relationships to taxon-specific anatomical ontologies, allowing integration of functional, phenotype and expression data.
PO / Plant Ontology
Aids to create structured controlled vocabularies, arranged in ontologies, that can be applied to plant-based database information. PO brings an integrated approach of adopting common annotation standards and a set of reference ontologies for plants. The project is a collaborative project that depends on coordination with several national and international projects.
Aims to describe lesions that arise in laboratory mice. MPATH was constructed ab initio by a group of clinical and veterinary pathologists in 2000. It has been used for the MoDIS database to capture and investigate pathology data from a massive aging expriment which has systematically phenotyped 31 of the most important inbred mouse strains.
WPO / Worm Phenotype Ontology
Allows the curation of C. elegans phenotypes. WPO includes phenotypic data from other nematode species. It contains streamlined version of the ontology that provides a subset of the terms in the whole ontology. The terminology aims to help integration of data from many different sources into a common body of knowledge, and to facilitate data mining and comparisons across species.
CMO / Colony Morphology Ontology
Permits to characterize the main features of the morphology of bacterial colonies. CMO allows the sharing of current understanding of the variation of colony morphology in microbial infection among domain experts, both clinicians and researchers. The ontology is useful for information retrieval applications, providing vocabulary and taxonomy that can be used for query expansion and semantic searching in this domain.
DPO / Drosophila Phenotype Ontology
Provides terms to curate phenotypes affecting behaviour and biological processes such as cell division of Drosophila melanogaster. DPO is limited to about 200 high-level and commonly described phenotypic classes. The terminology increases the possibilities for sophisticated and accurate queries to be made against the very large, rich dataset of DPO annotations curated and maintained by FlyBase.
APO / Ascomycete Phenotype Ontology
Provides hierarchically structured terms for the phenotypes of Ascomycete fungi.
FLOPO / FLOra Phenotype Ontology
Aids users to integrate and analyze the information contained in Floras. FLOPO permits description of traits of plant species found in Floras. It allows integration of qualitative trait data from different sources, including: text-based descriptions of phenotypes, image-based representations of plant traits such as those found in photos and specimen scans, as well as information about traits and phenotypes in trait databases.
FYPO / Fission Yeast Phenotype Ontology
Provides consistent computable descriptions of phenotype data in fission yeast. FYPO uses several existing ontologies from the open biological and biomedical ontologies (OBO) collection. It organizes terms along three axes: one axis distinguishes normal from abnormal phenotypes, a second axis classifies phenotypes by the entity affected, and the last one axis distinguishes phenotypes relevant at the level of a cell are from those that can be observed only in a population of cells.
OMP / Ontology of Microbial Phenotypes
Aims to capture phenotypes in a set of appropriately defined fields containing accessions or free text. OMP is a controlled vocabulary and structured language where all terms are well-defined representations of microbial phenotypes. It can be useful to annotate phenotypes associated with Escherichia coli genes and strains. The terminology is built using foundations provided by Basic Formal Ontology (BFO) and Phenotype and Trait Ontology (PATO).
CMPO / Cellular Microscopy Phenotype Ontology
Provides about 360 phenotype terms. CMPO can be used to annotate mitotic phenotypes observed in live human cells, as well as cellular phenotypes from tissue microarrays of diseased tissues from both human patients and mouse models. It describes a cell population phenotype as a collection of qualities that inhere in a population of cells. The database follows many standard conventions from the open biological and biomedical ontologies (OBO) foundry for ontology term metadata.
TOP / Thesaurus Of Plant characteristics
Serves for major plant characteristics used in functional ecology. TOP covers about 850 plant characteristics building on existing standards defined in the context of terminological initiatives. It can be used to describe plant traits and environmental associations and provides simple semantic relationships among these concepts.
ORDO / Orphanet Rare Disease Ontology
Serves for rare diseases derived from the Orphanet database. ORDO spots relationships between diseases, genes and other relevant features.
RS / Rat Strain ontology
Assists users to perform annotation on rat strains in a standardized manner. RS reflects the breeding history and genetic makeup of the strains to simplify querying and retrieval, analysis and comparisons amongst strains. The ontology can be used to classify all of the wild type, heterozygous, and homozygous strains, with the mutants further grouped under these strain subtypes. It also can serve for predicting the genomic contents a particular strain may have inherited from the parental strains.
CCO / Cell Component Ontology
Intends to describe the cellular architecture of a unicellular organism, or a cell type from a multicellular organism as well as the particular cellular components from which a specific type of cell is built. CCO includes about 160 terms containing a common-name and a definition. Many terms includes synonyms, a reference for the definition, terms and a 'sensu' slot to indicate organisms related taxonomic class.
eNanoMapper ontology
Aims to develop a comprehensive ontology and annotated database for the nanosafety domain to address the challenge of supporting the unified annotation of nanomaterials. eNanoMapper ontology was created by pan-European computational infrastructure for toxicological data management for engineered nanomaterials (ENMs).
GBOL / Genome Biology Ontology Language
Provides the means to describe computationally inferred genome annotations of biological objects typically found in a genome sequence annotation data file. GBOL is modular in design, extendible and linked to existing ontologies. Additionally, it can describe the linked data provenance of the extraction process of genetic information from genome sequences. GBOL is available under ontology and API format.
AtgO / Autophagy Ontology
Provides a first-generation hierarchical model of autophagy. AtgO is based on publicly available molecular interaction networks in S. cerevisiae. It contains up-to-date biological findings and a compendium of networks of nine different data types, including protein interactions, genetic interactions, gene co-expression, and gene-gene similarity based on shared protein sequence and structural information.
BAO / BioAssay Ontology
Standardizes, organizes and semantically defines biological assays and screening results. BAO provides a foundation for standardizing assay descriptions and endpoints. The ontology serves as a knowledge model by describing screening experiments and results semantically using description logic. It opens new functionality for querying and analyzing high-throughput screening (HTS) datasets. Users can query PubChem data using BAO terminology and collect sets of results for further analysis.
DINTO / Drug-Drug Interactions Ontology
Provides a comprehensive ontology for drug−drug interactions (DDI). DINTO aims to organize all DDI related knowledge and furnishes a wide range of DDI mechanisms as well as different subtypes of PD and PK mechanism types. The ontology was build according to the Neon methodology for ontology development and the OBO Foundry.
NCRO / Non-Coding RNA Ontology
Aims to integrate genomic and sequence-based annotation with gene expression regulation, secondary and 3D structure information, protein interactions, and their inter-relationships. NCRO consists in a standardized resource for: (1) annotating data about all forms of non-coding RNAs (ncRNAs) and (2) facilitating knowledge capture in the ncRNA domain. This ontology is useful to better understand unification of ncRNA biology.
CDAO / Comparative Data Analysis Ontology
Provides semantic descriptions of data and transformations for evolutionary comparative analysis. CDAO is an open source repository which provides terms for continuous and discrete characters and a part of its several subclasses. It proposes a general framework for describing the relationships between taxa, characters, states, their matrices, and associated phylogenies. It aims improve data interoperability in evolutionary methods.
Provides an OWL ontology for nuclear magnetic resonance (NMR) data inspired by mzML, the Proteomics Standard Initiatives’ (PSI) standard format established for mass spectrometry data. nmrCV is composed of over 600 classes, including imported entries from ontologies such as Chebi, PSI-MS or OBI. It includes common and essential NMR terms organized by following a simple taxonomy coupled to mild Description Logics (DL) axiomatisations to key classes.
MCO / Microbial Conditions Ontology
Aims to standardize the annotation of experimental conditions in microbial data repositories. MCO provides growth conditions terms together with their definitions, synonyms, references, and higher-level relations. The terms offered by the ontology can unambiguously define and tag each attribute of a particular experimental condition in order to systematize the annotation. It was created with simple ontological terms to describe elementary components.
SIO / Semanticscience Integrated Ontology
Provides classes and relations to describe and relate objects, processes and their attributes with specific extensions in the biomedical domain. SIO’s data concern spatial and temporal qualitative reasoning including location, containment, overlap, parthood and topology; participation and agency, linguistic and symbolic representation, as well as comparative and other information-oriented relations.
OMIT / Ontology for MIcroRNA Target prediction
Encodes in a standardized manner miR domain knowledge. OMIT is a semi-automated ontology which makes use of machine intelligence, considers miR domain-dependent and domain-independent properties/relationships. The ontology is composed of over 2 300 concepts, about 40 properties, and 90 relationships. It connects terms into each other and forms a directed acyclic graph (DAG).
Provides four orthogonal ontologies. eVOC aims to provide an appropriately detailed set of terms for describing the sample source of cDNA and SAGE libraries and labeled target cDNAs for microarray experiments. It can be used to identify not only tissue-specific spliceforms, but also splicing that is specific to certain developmental stages, cell types, and pathological states, or any combination of these states.
DTO / Drug Target Ontology
Provides a standardized ontology for drug targets that aims to facilitate the integration of diverse drug discovery information from various resources. DTO is organized around the class hierarchies of the four Illuminating the Druggable Genome (IDG) protein families, G protein–coupled receptors (GPCRs), kinases, ion channels, and nuclear hormone receptors. This terminology is composed of protein classes related to tissue and disease according to different levels of confidence.
MIM notation / Molecular Interaction Maps notation
Provides a list of convention for annotating and organize relationships in bioregulatory systems. MIM notation describes the relationships between multiple entities by using interactions glyphs, a controlled vocabulary and typographical convention. The system is able to display complex set of regulatory network interconnections or to capture different cell types and cell states. It also allows the specification of known molecular data as well as the addition of contingencies.
DrOn / Drug Ontology
Consists in a Web Ontology Language representation of drug products and their ingredients, mechanisms of action, strengths, and dose forms. DrOn aims to support analyses of large, drug-related datasets such as pharmacy claims and electronic health record (EHR) data. A version without Pittsburgh National Drug Codes (NDCs) is also available.
The ROS ontology / The Radiation Oncology Structures ontology
Standardizes the integration of radiation oncology data into clinical data warehouses for multicentric studies. The ROS ontology describes commonly contoured (anatomical and treatment planning) structures. It fits the specific needs of radiotherapy, while being aligned to existing ontologies. 22000 structures labels were extracted, classified and categorized to produce this ontology. Lymph nodes delineation international guidelines are provided.
Consists of an ontology based on the GENIA corpus and ontology, a set of about 2000 annotated abstracts from MEDLINE database concerning “transcription factors in human blood cells”. xGENIA contains original taxonomy of categories, biological entities as individuals, relations between individuals and links to the UMLS Metathesaurus concepts. The ontology can be used as a golden standard and a knowledge base for biological information extraction. It can be useful for researchers who design and test applications in the field of biological information extraction.
COMODI / COmputational MOdels DIffer
Serves for the annotation of differences between versions of a computational model in the life sciences. COMODI is an ontology that can be used for annotating changes, predicting the effects of changes on the simulation result, and filtering versions of a model for specific differences. It enables software to automatically filter the list of changes to show only the relevant changes for a given question.
Provides standardized and integrated definitions, descriptions, and their relations for the relevant lifelog concept domain. MELLO is an ontology for representing health-related lifelog data for covering general medical aspects with rich contents that support definitions, synonyms, and semantic relationships. Concepts were identified through a systematic enrichment and manual review process that founds lifelog terms sparsely scattered over standard sources including Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT) and Unified Medical Language System(UMLS).
Provides definitions for the foundational entities of biomedicine as a basic vocabulary to unambiguously describe facts in this domain. BIOTOP presents an ontologically sound layer for linking and integrating various specific domain ontologies. It can be used as top-level model for creating new ontologies for more specific domains or as aid for aligning or improving existing ones.
CATAMI / Collaborative and Automated Tools for Analysis of Marine Imagery
Provides a classification scheme for the analysis of marine imagery and video. CATAMI is an ontology for scoring marine biota and substrata in underwater imagery and intends to promote national consistency and standards for the classification. This tool uses a standardized combination of high-level taxonomy (phylum, order, class) and morphological attributes (shape, growth-form) given by the picture. CATAMI helps also to collate, display and analyze imagery collected for marine habitats.
EXACT / EXperimental ACTions
Provides an ontology for data recording of biomedical procedures. EXACT is designed to be directly integrated with other bio-medical ontologies. It is based on a framework that translate biomedical protocols from natural text to a machine amenable semantically-defined format. It proceeds by detecting and describing experimental actions and their descriptors in protocol texts and gives them unique IDs.
IAO / Information Artifact Ontology
Provides an ontology to simplify formally distinctions and commonalities between various sorts of information entities. IAO is an ontology of information entities that covers the same domain but are compiled independently from each other. The main elements of this tool are the representational unit (RU) and the representational artifact (RA). These core elements are designed to give the possibility to bridge between terminologies, concept systems and ontologies.
PATO / Phenotype And Trait Ontology
Provides an ontology of phenotypic qualities such as properties, attributes of characteristics. PATO is compatible with other ontologies like gene ontologies (GO) or anatomical ontologies to refer to phenotypes. It assigns logical definitions to improve phenotype ontologies by using phenotypic qualities and multiple additional ontologies from the Open Biological Ontologies (OBO) library.
FMA / Foundational Model of Anatomy
Provides an ontology for the symbolic representation of the phenotypic structure of the human body. FMA is initially based on the anatomical content of Unified Medical Language System (UMLS). This ontology is organized through four interrelated components: anatomy taxonomy (At), anatomical structural abstraction (ASA), anatomical transformation abstraction (ATA) and metaknowledge (Mk). It includes approximately 75 000 and up to 120 000 terms for over 2.1 million relationship instances.
AOPOntology / Adverse Outcome Pathway Ontology
Aims to facilitate knowledge-based inference of potential adverse outcomes using chemical screening and prioritization data from high content and high throughput assays. AOPOntology is a functional ontology that models Adverse Outcome Pathways (AOPs) as a parent class that contains classes for several different child AOP groupings. It builds on or imports several exiting ontologies, such as ChEBI, human phenotype ontology, or BioAssay Ontology and it also includes linkages to the Uniprot database.
PORO / Prolifera Ontology
Displays an anatomy ontology dealing with Porifera. PORO is a terminology that principally leans on the Thesaurus of Sponge Morphology, with the aim of extending its usabilty for character matrices construction for both modern and fossil taxa. This controlled vocabulary intends to link data about structural, functional, genetic, and gene expression data in sponges to improve researches about their morphological features as well as for further applications in molecular approaches.
PHAGE / Phylogenetics Ontology
Depicts phylogenetic analyses. PHAGE is an ontology, consisting of more than 45000 classes, which is partly collected from repositories including UniProtKB or Gene Ontology. This ontology is divided into seven pieces where each one stands for a phylogenic step and which is composed of a merging of resources annotations and programs.
PhylOnt / Phylogenetic Ontology
Describes phylogenetic analyses operations and its related metadata. PhlyOnt is a terminology intending to encompass methods dealing with phylogenic reconstruction to give users a resource for annotating both data and services in workflows. It includes programs and models as well as the possibility to incorporate associated from various sources. This ontology aims to simplify access and exchange of materials of phylogenetic studies.
SAO / Subcellular Anatomy Ontology
Intends to represent structures according their dimensional range. SAO is an ontology that aims to describe biological information dealing with cellular and subcellular structure, macromolecules as well as supracellular domains. This terminology is used by the Neuroscience Information Framework.
GEXO / Gene expression ontology
Offers a terminology of more than 89000 terms and about 450000 relationships dealing with gene expression. GEXO is an application ontology which have been built around information extracted from various repositories including Gene Ontology (GO) or the UniProt database. It can be used into knowledgebase project with the aim of increasing the speed of execution of complex queries. This terminology is part of the Gene eXpression Knowledge Base (GeXKB) tool.
HUPSON / Human Physiology Simulation Ontology
Intends to provide a support for biosimulation and algorithmic approaches. HUPSON furnishes a terminology, partly manually built, which aims to simplify interoperability between different methods as well as to assist users in text-mining tasks. This tool leans on the Basic Formal Ontology as well as on minimum information to reference an external ontology term (MIREOT) principles. It includes more than 2900 classes depicting human anatomical parts and physiological processes and about 7000 synonyms.
LDA / Ontology of Language Disorder in Autism
Deals with terms related with autism. LDA is a free terminology which items where extracted from an automatic curation from PubMed. It includes more than 30 classes and can be downloaded in three different formats.
EPSO / Epilepsy and Seizure Ontology
Encompasses domains related to epilepsy and epileptic seizures. EPSO offers an application ontology exploiting the four-dimensional epilepsy classification system and that is mainly dedicated to support clinical studies as well as epilepsy-focused informatics tools. It also can be used for constructing queries in order to identify patient cohorts. This ontology is used by the prevention and risk identification of sudden unexpected death in epilepsy mortality (PRISM) project.
EPILONT / Epilepsy Ontology
Depicts domains linked to epilepsy and epileptic seizures. EPILONT is a terminology including more than 130 classes, built around the International League Against Epilepsy (ILAE) diagnosis. It is exploited by the evolving platform for improving the living expectations of patients suffering from IctAl events (EPILEPSIAE) project.
miRNAO / microRNA Ontology
Consists of an application ontology for microRNAs. miRNAO can be applied to any database, or related tool, that contains or uses information on microRNAs as well as the regulation of gene expression that these mediate. The ontology follows the rules set by the OBO Foundry, in particular, the one of orthogonality. It aims to facilitate interoperability and reusability across different knowledge areas.
Consists of an ontology that represents pharmacogenomics (PGx) knowledge units and their components. PGxO has two main objectives: reconciling and tracing the PGx knowledge units. This ontology is designed to structure knowledge extracted from various sources such as reference databases (i.e. PharmGKB), literature, clinical guidelines or electronic health records (EHR)+biobank studies.
ORNASEQ / Ontology of RNA SEQuencing
Consists of a terminology designed for RNA sequencing. ORNASEQ is based on the ontology for biomedical investigations (OBI). It supplies a list of about 160 terms, some of the terms are from several existing ontologies, and more than 20 terms that have been added to OBI. This ontology is useful for the annotation of RNA-based next-generation sequencing and DNA-based next-generation sequencing data.