Ananiadou Sophia, Kell Douglas B, Tsujii Jun-ichi
School of Computer Science, National Centre for Text Mining, The Manchester Interdisciplinary Biocentre, The University of Manchester, 131 Princess Street, Manchester M1 7ND, UK.
Trends Biotechnol. 2006 Dec;24(12):571-9. doi: 10.1016/j.tibtech.2006.10.002. Epub 2006 Oct 12.
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.
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。
