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Ontology databases | Biomedical text mining

Ontology repositories include database and information repositories that help describe, classify, or clusterize biological entities.

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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.
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.
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.
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.
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.
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An open repository of biomedical ontologies that provides access via Web services and Web browsers to ontologies developed in OWL, RDF, OBO format and Protege frames. BioPortal functionality includes the ability to browse, search and visualize ontologies. The Web interface also facilitates community-based participation in the evaluation and evolution of ontology content by providing features to add notes to ontology terms, mappings between terms and ontology reviews based on criteria such as usability, domain coverage, quality of content, and documentation and support. Thus, BioPortal not only provides investigators, clinicians, and developers 'one-stop shopping' to programmatically access biomedical ontologies, but also provides support to integrate data from a variety of biomedical resources.
A linked data server designed for ontologies. Ontobee is aimed to facilitate ontology data sharing, visualization, query, integration, and analysis. Ontobee dynamically dereferences and presents individual ontology term URIs to (i) HTML web pages for user-friendly web browsing and navigation, and to (ii) RDF source code for Semantic Web applications. Ontobee is the default linked data server for most OBO Foundry library ontologies. Ontobee has also been used for many non-OBO ontologies.
Planteome database
Gathers a suite of interconnected reference ontologies. Planteome database’s terminologies are employed for the annotation of plant gene expression data, traits, phenotypes, genomes and germplasm, across 95 plant taxa. It contains species-specific Crop Ontologies (CO) and phenotype scoring standards. This database can assist in identification of traits of interest, and locates data, including germplasm, quantitative trait locus (QTL) and genes associated with a given trait.
NCBI disease corpus
A collection of 793 PubMed abstracts fully annotated at the mention and concept level to serve as a research resource for the biomedical natural language processing community. Each PubMed abstract was manually annotated by two annotators with disease mentions and their corresponding concepts in Medical Subject Headings (MeSH®) or Online Mendelian Inheritance in Man (OMIM®). Manual curation was performed using PubTator, which allowed the use of pre-annotations as a pre-step to manual annotations.
Provides reasoning services for bio-ontologies. Aber-OWL consists of an ontology repository, a set of web services and web interfaces that enable ontology-based semantic access to biological data and literature. Aber-OWL provides a framework for automatically accessing information that is annotated with ontologies or contains terms used to label classes in ontologies. When using Aber-OWL, access to ontologies and data annotated with them is not merely based on class names or identifiers but rather on the knowledge the ontologies contain and the inferences that can be drawn from it.
CIO / Confidence Information Ontology
Provides an ontology to capture confidence information about annotation assertions in a more systematic manner. The CIO is an ontology created to address the main points identified to provide clear and meaningful information about confidence in annotations. The CIO structure is made of two branches: (i) the confidence information statement branch, that contains the terms to be used by annotators and (ii) the confidence information element branch, that contains terms representing the intrinsic properties of the CI statements. CI statements are simply pre-composed using CI elements.
Develops next generation semantics-aware data management systems that are based on a synthesis of ontological reasoning and database management principles. DBonto incorporate techniques from many other areas of computer science, particularly those that give a complementary view of "Big Data" management, such as algorithms and machine learning, stream processing, and information retrieval. At the same time, this database aims to make important contributions to the career development of the next generation of research leaders.
Allows automated recognition of disease mentions, and studied the effect of various techniques in improving the normalization results based on the dictionary lookup approach. DiseaseExtract includes two broad stages: (i) extracting disease mentions from free text–a task referred to as disease named entity recognition (DNER) and (ii) normalizing the recognized mentions to standard controlled vocabularies such as MeSH–a task referred to as disease name normalization (DNORM).
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