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文本挖掘及其在系统生物学中的潜在应用。

Text mining and its potential applications in systems biology.

作者信息

Ananiadou Sophia, Kell Douglas B, Tsujii Jun-ichi

机构信息

School of Computer Science, National Centre for Text Mining, The Manchester Interdisciplinary Biocentre, The University of Manchester, 131 Princess Street, Manchester M1 7ND, UK.

出版信息

Trends Biotechnol. 2006 Dec;24(12):571-9. doi: 10.1016/j.tibtech.2006.10.002. Epub 2006 Oct 12.

Abstract

With biomedical literature increasing at a rate of several thousand papers per week, it is impossible to keep abreast of all developments; therefore, automated means to manage the information overload are required. Text mining techniques, which involve the processes of information retrieval, information extraction and data mining, provide a means of solving this. By adding meaning to text, these techniques produce a more structured analysis of textual knowledge than simple word searches, and can provide powerful tools for the production and analysis of systems biology models.

摘要

随着生物医学文献每周以数千篇的速度增长,要跟上所有的发展是不可能的;因此,需要自动化手段来管理信息过载。文本挖掘技术涉及信息检索、信息提取和数据挖掘过程,提供了一种解决这一问题的方法。通过为文本添加语义,这些技术比简单的单词搜索能对文本知识进行更结构化的分析,并且能为系统生物学模型的构建和分析提供强大工具。

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