Additional text has been included in Conclusion and future work section: The proposed methods encourage future work of implementing the same for full-text articles to elucidate many more relations from Biomedical literature.
Recent research has highlighted the need to automatically mine such information from the biomedical literature, and approaches for extraction of mutations and their associated genes from natural language text have been proposed (4 9).
Despite extensive efforts to automatically analyze various aspects of biomedical text, there have been only few studies focusing on anatomical entities, and no dedicated methods for learning to automatically recognize anatomical entity mentions in free-form text have been introduced.
The application of Natural Language Processing NLPP) techniques to mine ADRs from texts has been recently considered with encouraging results, mostly in the issue of drug product labels [ 11- 13], biomedical literature [ 14], medical case reports [ 15] and health records [ 16, 17].
iSimp is designed to simplify complex sentences commonly found in the biomedical text, and has been shown to improve existing text mining applications that rely on the analysis of sentence structures.
As biomedical literature on servers grows exponentially in the form of semi-structured documents, biomedical text mining has been intensively investigated to find information in a more accurate and efficient manner.
Although syntactic alternations in biomedical text have not previously been studied, there are some precedents in the biomedical domain for work on the larger question of biomedical verbal argument structures.
In spite of significant advancements in text- and data-mining techniques, the vast knowledge space of biomarkers in biomedical text has remained unexplored.
BioNLP, or the application of natural processing to biomedical texts, primarily for purposes of text mining, has been a burgeoning area of research both within the computational linguistics community and within bioinformatics and computational biology.
