TY - GEN
T1 - Intelligent agent system for bio-medical literature mining
AU - Islam, Md Tawhidul
AU - Bollina, Durgaprasad
AU - Nayak, Abhaya
AU - Ranganathan, Shoba
N1 - Copyright 2007 IEEE. Reprinted from Proceedings of the international conference on information and communication technology (ICICT2007). This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Macquarie University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=34748877216&partnerID=8YFLogxK
U2 - 10.1109/ICICT.2007.375342
DO - 10.1109/ICICT.2007.375342
M3 - Conference proceeding contribution
AN - SCOPUS:34748877216
SN - 9843233948
SN - 9789843233943
SP - 57
EP - 63
BT - ICICT 2007: Proceedings of International Conference on Information and Communication Technology
A2 - Kabir, S. M. Lutful.
PB - ICICT
CY - Dhaka, Bangladesh
T2 - ICICT 2007: International Conference on Information and Communication Technology
Y2 - 7 March 2007 through 9 March 2007
ER -