An automated identification and analysis of ontological terms in gastrointestinal diseases and nutrition-related literature provides useful insights

Koci, O., Logan, M. , Svolos, V., Russell, R. K., Gerasimidis, K. and Ijaz, U. Z. (2018) An automated identification and analysis of ontological terms in gastrointestinal diseases and nutrition-related literature provides useful insights. PeerJ, 6, e5047. (doi: 10.7717/peerj.5047) (PMID:30065857) (PMCID:PMC6064635)

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Abstract

With an unprecedented growth in the biomedical literature, keeping up to date with the new developments presents an immense challenge. Publications are often studied in isolation of the established literature, with interpretation being subjective and often introducing human bias. With ontology-driven annotation of biomedical data gaining popularity in recent years and online databases offering metatags with rich textual information, it is now possible to automatically text-mine ontological terms and complement the laborious task of manual management, interpretation, and analysis of the accumulated literature with downstream statistical analysis. In this paper, we have formulated an automated workflow through which we have identified ontological information, including nutrition-related terms in PubMed abstracts (from 1991 to 2016) for two main types of Inflammatory Bowel Diseases: Crohn’s Disease and Ulcerative Colitis; and two other gastrointestinal (GI) diseases, namely, Coeliac Disease and Irritable Bowel Syndrome. Our analysis reveals unique clustering patterns as well as spatial and temporal trends inherent to the considered GI diseases in terms of literature that has been accumulated so far. Although automated interpretation cannot replace human judgement, the developed workflow shows promising results and can be a useful tool in systematic literature reviews. The workflow is available at https://github.com/KociOrges/pytag.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Russell, Dr Richard and Logan, Dr Michael and Svolos, Dr Vaios and Gerasimidis, Professor Konstantinos and Ijaz, Dr Umer and Koci, Orges
Authors: Koci, O., Logan, M., Svolos, V., Russell, R. K., Gerasimidis, K., and Ijaz, U. Z.
College/School:College of Medical Veterinary and Life Sciences > School of Medicine, Dentistry & Nursing
College of Science and Engineering > School of Engineering > Infrastructure and Environment
College of Medical Veterinary and Life Sciences > School of Infection & Immunity
Journal Name:PeerJ
Publisher:PeerJ
ISSN:2167-8359
ISSN (Online):2167-8359
Published Online:26 July 2018
Copyright Holders:Copyright © 2018 Koci et al.
First Published:First published in PeerJ 6: e5047
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
652771Understanding microbial community through in situ environmental 'omic data synthesisUmer Zeeshan IjazNatural Environment Research Council (NERC)NE/L011956/1ENG - ENGINEERING INFRASTRUCTURE & ENVIR