Text mining and its potential applications in systems biology

被引:206
作者
Ananiadou, Sophia
Kell, Douglas B.
Tsujii, Jun-ichi
机构
[1] Univ Manchester, Manchester Interdisciplinary Bioctr, Sch Comp Sci, Natl Ctr Text Min, Manchester M1 7ND, Lancs, England
[2] Univ Manchester, Sch Chem, Manchester M60 1QD, Lancs, England
[3] Univ Manchester, Manchester Interdisciplinary Bioctr, Manchester Ctr Integrat Syst Biol, Manchester M1 7ND, Lancs, England
[4] Univ Tokyo, Dept Comp Sci, Bunkyo Ku, Tokyo 1130033, Japan
基金
英国生物技术与生命科学研究理事会; 英国工程与自然科学研究理事会;
关键词
D O I
10.1016/j.tibtech.2006.10.002
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
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.
引用
收藏
页码:571 / 579
页数:9
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