Oct 8, 2018

Ontology based mining of pathogen-disease associations from literature

BioRxiv : the Preprint Server for Biology
Senay Kafkas, Robert Hoehndorf


Background: Infectious diseases claim millions of lives especially in the developing countries each year, and resistance to drugs is an emerging threat worldwide. Identification of causative pathogens accurately and rapidly plays a key role in the success of treatment. To support infectious disease research and mechanisms of infection, there is a need for an open resource on pathogen-disease associations that can be utilized in computational studies. A large number of pathogen-disease associations is available from the literature in unstructured form and we need automated methods to extract the data. Results: We developed a text mining system designed for extracting pathogen-disease relations from literature. Our approach utilizes background knowledge from an ontology and statistical methods for extracting associations between pathogens and diseases. In total, we extracted a total of 3,420 pathogen-disease associations from literature. We integrated our literature-derived associations into a database which links pathogens to their phenotypes for supporting infectious disease research. Conclusions: To the best of our knowledge, we present the first study focusing on extracting pathogen-disease associations from publications. We ...Continue Reading

  • References
  • Citations


  • We're still populating references for this paper, please check back later.
  • References
  • Citations


  • This paper may not have been cited yet.

Mentioned in this Paper

Pathogenic Organism
Pharmacologic Substance
Statistical Technique
Gene Ontology Project
Computational Technique
Gene Ontology
Communicable Diseases

About this Paper

Related Feeds

BioRxiv & MedRxiv Preprints

BioRxiv and MedRxiv are the preprint servers for biology and health sciences respectively, operated by Cold Spring Harbor Laboratory. Here are the latest preprint articles (which are not peer-reviewed) from BioRxiv and MedRxiv.