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Updated: Jan 23, 2026

Author Spotlight: Advancing Pathogen Detection and Disease Assessment in Real-Time Using M-ROSE
Published on: March 1, 2024
PathoPhenoDB, linking human pathogens to their phenotypes in support of infectious disease research
Şenay Kafkas1, Marwa Abdelhakim1, Yasmeen Hashish1
1Computer, Electrical and Mathematical Sciences & Engineering with Division, Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, 23955, Saudi Arabia.
Abstract:
Understanding the relationship between the pathophysiology of infectious disease, the biology of the causative agent and the development of therapeutic and diagnostic approaches is dependent on the synthesis of a wide range of types of information. Provision of a comprehensive and integrated disease phenotype knowledgebase has the potential to provide novel and orthogonal sources of information for the understanding of infectious agent pathogenesis, and support for research on disease mechanisms. We have developed PathoPhenoDB, a database containing pathogen-to-phenotype associations. PathoPhenoDB relies on manual curation of pathogen-disease relations, on ontology-based text mining as well as manual curation to associate host disease phenotypes with infectious agents. Using Semantic Web technologies, PathoPhenoDB also links to knowledge about drug resistance mechanisms and drugs used in the treatment of infectious diseases. PathoPhenoDB is accessible at http://patho.phenomebrowser.net/ , and the data are freely available through a public SPARQL endpoint.
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