Event extraction for systems biology by text mining the literature

被引：137

作者：

Ananiadou, Sophia ^{[1
,2
]}

Pyysalo, Sampo ^{[3
]}

Tsujii, Jun'ichi ^{[1
,2
,3
]}

Kell, Douglas B. ^{[4
]}

机构：

[1] Univ Manchester, Sch Comp Sci, Manchester M13 9PL, Lancs, England

[2] Univ Manchester, Manchester Interdisciplinary Bioctr, Natl Ctr Text Min, Manchester M1 7DN, Lancs, England

[3] Univ Tokyo, Dept Comp Sci, Bunkyo Ku, Tokyo 1130033, Japan

[4] Univ Manchester, Sch Chem, Manchester M1 7DN, Lancs, England

来源：

TRENDS IN BIOTECHNOLOGY | 2010年 / 28卷 / 07期

基金：

英国生物技术与生命科学研究理事会;

关键词：

PROTEIN-PROTEIN INTERACTIONS; NAMED ENTITIES; SEARCH ENGINE; INFORMATION; NETWORK; DATABASE; CORPUS; ANNOTATION; PATHWAYS; SCIENCE;

D O I：

10.1016/j.tibtech.2010.04.005

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：

Systems biology recognizes in particular the importance of interactions between biological components and the consequences of these interactions. Such interactions and their downstream effects are known as events. To computationally mine the literature for such events, text mining methods that can detect, extract and annotate them are required. This review summarizes the methods that are currently available, with a specific focus on protein protein interactions and pathway or network reconstruction. The approaches described will be of considerable value in associating particular pathways and their components with higher-order physiological properties, including disease states.

引用

页码：381 / 390

页数：10

共 82 条

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