Intelligent Agent System for Bio-medical Literature Mining

With the advances of World Wide Web technology and advanced research in bioinformatics and systems biology domain has highlighted the increasing need for automatic information extraction [IE] system to extract information from scientific literature databases. Extraction of scientific information in biomedical articles is a central task for supporting biomarker discovery efforts. In this paper, we propose an algorithm that is capable of extracting scientific information on biomarker like gene, genome, disease, allele, cell etc from the text by finding out the focal topic of the document and extracting the most relevant properties of that topic. The topic and its properties are represented as semantic networks and then stored in a database. This IE algorithm will extract the most important biological terms and relation by statistical and pattern matching NLP techniques. This IE tool expected to help the researchers to get the latest information on biomarker discovery and its other biomedical research advances. We show preliminary results, demonstrating that the method has a strong potential to biomarker discovery methods.