Gene name disambiguation usingmulti-scope species detection

Jui Chen Hsiao, Chih Hsuan Wei, Hung Yu Kao

研究成果: Article同行評審

1 引文 斯高帕斯(Scopus)

摘要

Species detection is an important topic in the text mining field. According to the importance of the research topics (e.g., species assignment to genes and document focus species detection), some studies are dedicated to an individual topic. However, no researcher to date has discussed species detection as a general problem. Therefore, we developed a multi-scope species detection model to identify the focus species for different scopes (i.e., gene mention, sentence, paragraph, and global scope of the entire article). Species assignment is one of the bottlenecks of gene name disambiguation. In our evaluation, recognizing the focus species of a gene mention in four different scopes improved the gene name disambiguation. We used the species cue words extracted from articles to estimate the relevance between an article and a species. The relevance score was calculated by our proposed entities frequency-augmented invert species frequency (EF-AISF) formula, which represents the importance of an entity to a species. We also defined a relation guide factor (RGF) to normalize the relevance score. Our method not only achieved better performance than previous methods but also can handle the articles that do not specifically mention a species. In the DECA corpus, we outperformed previous studies and obtained an accuracy of 88.22 percent.

原文English
文章編號6654152
頁(從 - 到)55-62
頁數8
期刊IEEE/ACM Transactions on Computational Biology and Bioinformatics
11
發行號1
DOIs
出版狀態Published - 2014

All Science Journal Classification (ASJC) codes

  • 生物技術
  • 遺傳學
  • 應用數學

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