Ontology-based Brucella vaccine literature indexing and systematic analysis of gene-vaccine association network

BMC Immunology

Research Article

Junguk Hur¹  Eva L Feldman²  Yongqun He³  Zuoshuang Xiang⁴ 

[1] Bioinformatics Program, University of Michigan, 48109, Ann Arbor, MI, USA;Department of Neurology, University of Michigan, 48109, Ann Arbor, MI, USA;Bioinformatics Program, University of Michigan, 48109, Ann Arbor, MI, USA;Department of Neurology, University of Michigan, 48109, Ann Arbor, MI, USA;National Center for Integrative Biomedical Informatics, University of Michigan, 48109, Ann Arbor, MI, USA;Bioinformatics Program, University of Michigan, 48109, Ann Arbor, MI, USA;Unit for Laboratory Animal Medicine, University of Michigan, 48109, Ann Arbor, MI, USA;National Center for Integrative Biomedical Informatics, University of Michigan, 48109, Ann Arbor, MI, USA;Department of Microbiology and Immunology, University of Michigan, 48109, Ann Arbor, MI, USA;Unit for Laboratory Animal Medicine, University of Michigan, 48109, Ann Arbor, MI, USA;

关键词: Brucellosis;    Protective Antigen;    Literature Mining;    Biomedical Ontology;    Brucella Abortus;   

DOI  :  10.1186/1471-2172-12-49

 received in 2011-06-02, accepted in 2011-08-26,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundVaccine literature indexing is poorly performed in PubMed due to limited hierarchy of Medical Subject Headings (MeSH) annotation in the vaccine field. Vaccine Ontology (VO) is a community-based biomedical ontology that represents various vaccines and their relations. SciMiner is an in-house literature mining system that supports literature indexing and gene name tagging. We hypothesize that application of VO in SciMiner will aid vaccine literature indexing and mining of vaccine-gene interaction networks. As a test case, we have examined vaccines for Brucella, the causative agent of brucellosis in humans and animals.ResultsThe VO-based SciMiner (VO-SciMiner) was developed to incorporate a total of 67 Brucella vaccine terms. A set of rules for term expansion of VO terms were learned from training data, consisting of 90 biomedical articles related to Brucella vaccine terms. VO-SciMiner demonstrated high recall (91%) and precision (99%) from testing a separate set of 100 manually selected biomedical articles. VO-SciMiner indexing exhibited superior performance in retrieving Brucella vaccine-related papers over that obtained with MeSH-based PubMed literature search. For example, a VO-SciMiner search of "live attenuated Brucella vaccine" returned 922 hits as of April 20, 2011, while a PubMed search of the same query resulted in only 74 hits. Using the abstracts of 14,947 Brucella-related papers, VO-SciMiner identified 140 Brucella genes associated with Brucella vaccines. These genes included known protective antigens, virulence factors, and genes closely related to Brucella vaccines. These VO-interacting Brucella genes were significantly over-represented in biological functional categories, including metabolite transport and metabolism, replication and repair, cell wall biogenesis, intracellular trafficking and secretion, posttranslational modification, and chaperones. Furthermore, a comprehensive interaction network of Brucella vaccines and genes were identified. The asserted and inferred VO hierarchies provide semantic support for inferring novel knowledge of association of vaccines and genes from the retrieved data. New hypotheses were generated based on this analysis approach.ConclusionVO-SciMiner can be used to improve the efficiency for PubMed searching in the vaccine domain.

【 授权许可】

Unknown   
© Hur et al; licensee BioMed Central Ltd. 2011. 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/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.