期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：10
DOI：10.15680/IJIRCCE.2015.0310131
出版社：S&S Publications
摘要：Authors frequently use different names to refer to the same gene or protein names across Bio-medical articles. Identifying the alternate names for the same gene/protein would help biologists in the process of gene-protein interactions and protein-protein interactions. Biomedical databases such as SWISSPROT, GenBank, GOLD, UniGene and Karyn's Geno me include synonyms, but these databases may not be always up -to-date. Therefore, it is necessary to automate this process, because of the increasing number of discovered genes and proteins. In this paper we co nsidered this problem as Natural Language processing (NLP) problem and solved using SSFPOA semantic measure. Experiments were conducted on Medline abstracts and results are compared with existing methods. Machi ne learning algorithms are used in our work to analyze the performance of our method. Results are evaluated with the help of performance measures and results showed high percentage of accuracy when compared with existing works
