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DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes.

DisGeNET is a comprehensive discovery platform designed to address a variety of questions concerning the genetic underpinning of human diseases. DisGeNET contains over 380,000 associations between >16,000 genes and 13,000 diseases, which makes it one of the largest repositories currently available of its kind. DisGeNET integrates expert-curated databases with text-mined data, covers information on Mendelian and complex diseases, and includes data from animal disease models. It features a score based on the supporting evidence to prioritize gene-disease associations. It is an open access resource available through a web interface, a Cytoscape plugin and as a Semantic Web resource. The web interface supports user-friendly data exploration and navigation. DisGeNET data can also be analysed via the DisGeNET Cytoscape plugin, and enriched with the annotations of other plugins of this popular network analysis software suite. Finally, the information contained in DisGeNET can be expanded and complemented using Semantic Web technologies and linked to a variety of resources already present in the Linked Data cloud. Hence, DisGeNET offers one of the most comprehensive collections of human gene-disease associations and a valuable set of tools for investigating the molecular mechanisms underlying diseases of genetic origin, designed to fulfill the needs of different user profiles, including bioinformaticians, biologists and health-care practitioners. Database URL: http://www.disgenet.org/

Pubmed ID: 25877637 RIS Download

Mesh terms: Animals | Cloud Computing | Databases, Genetic | Disease Models, Animal | Gene Regulatory Networks | Genetic Diseases, Inborn | Genome, Human | Humans | Internet | User-Computer Interface

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


NCI Thesaurus

A reference terminology and core biomedical ontology for NCI that covers approximately 100,000 key biomedical concepts with terms, codes, definitions, and more than 200,000 inter-concept relationships. It is the reference terminology for NCI, NCI Metathesaurus and NCI informatics infrastructure covering vocabulary for clinical care, translational and basic research, and public information and administrative activities. It includes broad coverage of the cancer domain, including cancer related diseases, findings and abnormalities; anatomy; agents, drugs and chemicals; genes and gene products and so on. In certain areas, like cancer diseases and combination chemotherapies, it provides the most granular and consistent terminology available. It combines terminology from numerous cancer research related domains, and provides a way to integrate or link these kinds of information together through semantic relationships. NCIt features: * Stable, unique codes for biomedical concepts; * Preferred terms, synonyms, definitions, research codes, external source codes, and other information; * Links to NCI Metathesaurus and other information sources; * Over 200,000 cross-links between concepts, providing formal logic-based definition of many concepts; * Extensive content integrated from NCI and other partners, much available as separate NCIt subsets * Updated frequently by a team of subject matter experts. NCIt is a widely recognized standard for biomedical coding and reference, used by a broad variety of public and private partners both nationally and internationally including the Clinical Data Interchange Standards Consortium Terminology (CDISC), the U.S. Food and Drug Administration (FDA), the Federal Medication Terminologies (FMT), and the National Council for Prescription Drug Programs (NCPDP).

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DisGeNET

Database and discovery platform integrating information on gene-disease, and variant-disease associations from several public data sources and the scientific literature. The current version contains associations between genes (and variants) and diseases, disorders and clinical or abnormal human phenotypes. A score is used to rank the associations based on the supporting evidence. DisGeNET can be queried through Search and Browse functionalities available from the web interface, or via a Cytoscape App, and using an R package (disgenet2r). The data can also be queried by downloading the SQLite database to a local repository. An RDF (Resource Description Framework) representation of DisGeNET database is also available. It can be queried using a SPARQL endpoint and a Faceted Browser.

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Plant enzymes and biochemical pathways database

The Plant Metabolic Network (PMN) is a collaborative project among databases and biochemists with a common goal to build a broad network of plant metabolic pathway databases. A central feature of the PMN is PlantCyc, a comprehensive plant biochemical pathway database, containing curated information from the literature and computational analyses about the genes, enzymes, compounds, reactions, and pathways involved in primary and secondary metabolism. The central goal of the Plant Metabolic Network (PMN) is to bring together biochemical pathway databases and research communities focused on plant metabolism. PMN will generate an infrastructure for drawing together diverse sources of plant metabolism information.

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UniProt

Resource for protein sequence and functional information that welcomes updates, corrections, and the submission of new protein sequence data. It is comprised of four components, each optimized for different uses. UniProt Knowledgebase (UniProtKB) is the central access point for curated protein information, including function, classification, and cross-reference, and contains two sections: UniProtKB/Swiss-Prot, which is manually annotated and reviewed; and UniProtKB/TrEMBL, which is automatically annotated and not reviewed. UniProt Reference Clusters (UniRef) are databases providing clustered sets of sequences from the UniProtKB and selected UniProt Archive records to obtain complete coverage of sequence space at several resolutions while hiding redundant sequences. UniProt Archive (UniParc) is a comprehensive repository used to keep track of sequences and their identifiers. UniProt Metagenomic and Environmental Sequences (UniMES) database is a repository specifically developed for metagenomic and environmental data.

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Reactome

Database for pathways and pathway annotations authored by expert biologists, in collaboration with Reactome editorial staff. The core unit of the Reactome data model is the reaction. Entities (nucleic acids, proteins, complexes and small molecules) participating in reactions form a network of biological interactions and are grouped into pathways. Examples of biological pathways in Reactome include signaling, innate and acquired immune function, transcriptional regulation, translation, apoptosis and classical intermediary metabolism. Reactome provides an intuitive website to navigate pathway knowledge and a suite of data analysis tools to support the pathway-based analysis of complex experimental and computational data sets.

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