基于文本挖掘的精子发生各阶段的相关基因/蛋白名称提取  

Extraction of Gene/Protein Names Involved in Each Stage of Spermatogenesis Based on Literature Mining

作　　者：朱俊[1,2] 殷建平[1] 赵志恒[1] 祝恩[1] 班荣军 

机构地区：[1]国防科学技术大学计算机学院,长沙410073 [2]西昌卫星发射中心,海南文昌571300 [3]南京大学计算机科学与技术系,南京210093

出　　处：《计算机研究与发展》2014年第6期1352-1358,共7页Journal of Computer Research and Development

基　　金：国家自然科学基金项目(60970034;61170287;61232016);高等学校全国优秀博士论文作者资助项目(2007B4)

摘　　要：精子发生是雄性哺乳动物生命活动中一个重要的生物学过程,该过程的每一个阶段都有众多基因/蛋白参与并发挥功能.相关基因/蛋白出现异常是导致男性不育症的主要诱因,但这些基因/蛋白的信息大都分散在科研文献中,而人工从海量文献中提取这些基因/蛋白名称费时费力,因此,基于文本挖掘技术,提出了自动提取精子发生过程各个阶段中发挥作用的基因/蛋白名称的策略.首先比较了3种不同算法在不同词条数目下的分类效果,并确定用支持向量机(support vector machine,SVM)算法对相关文本按照精子发生过程的3阶段分类,然后建立适当的信息提取和筛选方法,从文献摘要中提取每个阶段中的基因/蛋白名称.最后,通过与人工提取的基因/蛋白名称进行比较验证,提取结果的正确率为71.9%,证明了提取策略的可行性.Spermatogenesis is an important bioprocess in the lifetime of male mammalians,which has deep effect on mammal＇s reproduction.Abnormal spermatogenesis is a major cause of male infertility,however treatments for this are limited.Characterizing the genes/proteins involved in spermatogenesis is fundamental to understand the mechanisms underlying this biological process and to develop treatments for the problems in spermatogenesis.However,most crucial information of spermatogenesis-related genes/proteins scatters in vast amount of research articles,so manually curation of these genes/proteins could be a time-consuming task.In this paper,a novel strategy is proposed to automatically extract the names of spermatogenesis-related genes/proteins,which function in different stages of spermatogenesis based on literature mining.Firstly,it compares three different algorithms performance on different terms and applys an SVM classifier trained with a manually prepared dataset to classify spermatogenesis-related texts into three classes in accordance with the three stages of spermatogenesis.Then,integrating expert knowledge and grammar rules,it recongnizes and extracts the gene/protein names of each spermatogenesis stage with high confidence.Finally,a manually curation test dataset is used to test the performance of this strategy,and the strategy gets an accuracy of 71.9％,which verifys the reliability of proposed method and proves the value of application.

关 键 词：文本挖掘 精子发生 男性不育症 文本分类 基因 蛋白名称提取 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]