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Updated: Jun 18, 2026

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
Published on: October 13, 2023
Exploitation of ontological resources for scientific literature analysis: searching genes and related diseases
Antonio Jimeno-Yepes1, Rafael Berlanga-Llavori, Dietrich Rebholz-Schuhmann
1European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, U.K. yepes@ebi.ac.uk
Abstract:
Ontological resources such as controlled vocabularies, taxonomies and ontologies from the OBO foundry are used to represent biomedical domain knowledge. The development of such resources is a time consuming task. Once they are finished they contribute to standardization of information representation, interoperability of IT solutions, literature analysis and knowledge discovery. Text mining comprises IT solutions for information retrieval (IR) and information extraction (IE). IR technology exploits ontological resources to select documents that fit best to the processed query, for example, through indexing of the literature content with concept ids or through disambiguation of terms in the query. IE solutions make use of the ontological labels to identify concepts in the text. The text passages that denote conceptual entries are then used either to annotate named entities or to relate the named entities to each other. For knowledge discovery (KD) solutions the identified concepts in the scientific literature are used to relate entities to each other, e.g. to identify gene-disease relations based on shared molecular functions.
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