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
rDGIdb / Drug-Gene Interaction database
ImtRDB / the database for Imperfect interspersed Mtdna Repeats annotation
ML Repo / Microbiome Learning Repo
Protein Multiple Alignments
RTFDB / Rice Transcription Factor Phylogenomics Database
sncRNA Zoo
The human gut virome database
cAb-Rep / Curated Antibody Repertoires
ARS / Arabidopsis RNA-Seq database
Bovine Genome Database
CAD / Coronary Artery Disease
CGVD / Chinese Genomic Variation Database
ChlamDB / Chlamydiae Database
DrugCombDB / Drug Combinations Database
ENdb / Enhancers Database
MabeLLINI / Mycobacterium ABscessus modELLing INItiative
oRNAment / o RNA motifs enrichment in transcriptomes
BiGG Models
CLIPS / CLInical trial Protocol database System
FoodBase corpus
Mouse Phenome Database
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.