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A Knowledge-Driven Approach to Extract Disease-Related Biomarkers from the Literature
Joint Authors
Cases, M.
Bravo, À.
Furlong, L. I.
Sanz, F.
Queralt-Rosinach, N.
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-16
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The biomedical literature represents a rich source of biomarker information.
However, both the size of literature databases and their lack of standardization hamper the automatic exploitation of the information contained in these resources.
Text mining approaches have proven to be useful for the exploitation of information contained in the scientific publications.
Here, we show that a knowledge-driven text mining approach can exploit a large literature database to extract a dataset of biomarkers related to diseases covering all therapeutic areas.
Our methodology takes advantage of the annotation of MEDLINE publications pertaining to biomarkers with MeSH terms, narrowing the search to specific publications and, therefore, minimizing the false positive ratio.
It is based on a dictionary-based named entity recognition system and a relation extraction module.
The application of this methodology resulted in the identification of 131,012 disease-biomarker associations between 2,803 genes and 2,751 diseases, and represents a valuable knowledge base for those interested in disease-related biomarkers.
Additionally, we present a bibliometric analysis of the journals reporting biomarker related information during the last 40 years.
American Psychological Association (APA)
Bravo, À.& Cases, M.& Queralt-Rosinach, N.& Sanz, F.& Furlong, L. I.. 2014. A Knowledge-Driven Approach to Extract Disease-Related Biomarkers from the Literature. BioMed Research International،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-457636
Modern Language Association (MLA)
Bravo, À.…[et al.]. A Knowledge-Driven Approach to Extract Disease-Related Biomarkers from the Literature. BioMed Research International No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-457636
American Medical Association (AMA)
Bravo, À.& Cases, M.& Queralt-Rosinach, N.& Sanz, F.& Furlong, L. I.. A Knowledge-Driven Approach to Extract Disease-Related Biomarkers from the Literature. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-457636
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-457636