URL: | https://csbg.cnb.csic.es/CoMentG |
Full name: | Co-mentions between biological terms |
Description: | The CoMentG resource contains millions of relationships between terms of biomedical interest obtained from the scientific literature. At the core of the system is a methodology for detecting significant co-mentions of concepts in the entire PubMed corpus. That method was applied to nine sets of terms covering the most important classes of biomedical concepts: diseases, symptoms/clinical signs, molecular functions, biological processes, cellular compartments, anatomic parts, cell types, bacteria and chemical compounds. |
Year founded: | 2024 |
Last update: | 2024-04 |
Version: | v1.0 |
Accessibility: | |
Country/Region: | Spain |
Data type: | |
Data object: |
NA
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Database category: | |
Major species: |
NA
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Keywords: |
University/Institution: | Centro Nacional de Biotecnología |
Address: | C/ Darwin, 3 - Cantoblanco, 28049, Madrid,Spain |
City: | Madrid |
Province/State: | |
Country/Region: | Spain |
Contact name (PI/Team): | Florencio Pazos |
Contact email (PI/Helpdesk): | pazos@cnb.csic.es |
CoMentG: comprehensive retrieval of generic relationships between biomedical concepts from the scientific literature. [PMID: 38564426]
The CoMentG resource contains millions of relationships between terms of biomedical interest obtained from the scientific literature. At the core of the system is a methodology for detecting significant co-mentions of concepts in the entire PubMed corpus. That method was applied to nine sets of terms covering the most important classes of biomedical concepts: diseases, symptoms/clinical signs, molecular functions, biological processes, cellular compartments, anatomic parts, cell types, bacteria and chemical compounds. We obtained more than 7 million relationships between more than 74 000 terms, and many types of relationships were not available in any other resource. As the terms were obtained from widely used resources and ontologies, the relationships are given using the standard identifiers provided by them and hence can be linked to other data. A web interface allows users to browse these associations, searching for relationships for a set of terms of interests provided as input, such as between a disease and their associated symptoms, underlying molecular processes or affected tissues. The results are presented in an interactive interface where the user can explore the reported relationships in different ways and follow links to other resources. Database URL: https://csbg.cnb.csic.es/CoMentG/. |