Context-based resolution of semantic conflicts in biological pathways

BMC Medical Informatics and Decision Making

Research Article

Hasun Yu¹  Doheon Lee¹  Mijin Kwon¹  Sungji Choo¹  Seyeol Yoon¹  Kyunghyun Park¹  Dongjin Jang¹  Jinmyung Jung¹  Sangwoo Kim² 

[1] Department of Bio and Brain Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, 305-701, Daejeon, Republic of Korea;Severance Biomedical Science Institute, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 120-752, Seoul, Republic of Korea;

关键词: Pituitary Adenoma;    Acromegaly;    Context Information;    Biomedical Literature;    Pathway Database;   

DOI  :  10.1186/1472-6947-15-S1-S3

来源: Springer

【 摘 要 】

BackgroundInteractions between biological entities such as genes, proteins and metabolites, so called pathways, are key features to understand molecular mechanisms of life. As pathway information is being accumulated rapidly through various knowledge resources, there are growing interests in maintaining the integrity of the heterogeneous databases.MethodsHere, we defined conflict as a status where two contradictory pieces of evidence (i.e. 'A increases B' and 'A decreases B') coexist in a same pathway. This conflict damages unity so that inference of simulation on the integrated pathway network might be unreliable. We defined rule and rule group. A rule consists of interaction of two entities, meta-relation (increase or decrease), and contexts terms about tissue specificity or environmental conditions. The rules, which have the same interaction, are grouped into a rule group. If the rules don't have a unanimous meta-relation, the rule group and the rules are judged as being conflicting.ResultsThis analysis revealed that almost 20% of known interactions suffer from conflicting information and conflicting information occurred much more frequently in the literature than the public database.With consideration for dual functions depending on context, we thought it might resolve conflict to consider context. We grouped rules, which have the same context terms as well as interaction. It's revealed that up to 86% of the conflicts could be resolved by considering context.Subsequent analysis also showed that those contradictory records generally compete each other closely, but some information might be suspicious when their evidence levels are seriously imbalanced.ConclusionsBy identifying and resolving the conflicts, we expect that pathway databases can be cleaned and used for better secondary analyses such as gene/protein annotation, network dynamics and qualitative/quantitative simulation.

【 授权许可】

Unknown   
© Yoon et al.; licensee BioMed Central Ltd. 2015. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.