Event extraction for systems biology by text mining the literature

Sophia Ananiadou; Sampo Pyysalo; Jun'ichi Tsujii; Douglas B. Kell

doi:10.1016/j.tibtech.2010.04.005

Event extraction for systems biology by text mining the literature

Sophia Ananiadou, Sampo Pyysalo, Jun'ichi Tsujii, Douglas B. Kell

Research output: Contribution to journal › Article › peer-review

Abstract

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. © 2010 Elsevier Ltd.

Original language	English
Pages (from-to)	381-390
Number of pages	9
Journal	Trends in Biotechnology
Volume	28
Issue number	7
DOIs	https://doi.org/10.1016/j.tibtech.2010.04.005
Publication status	Published - Jul 2010

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@article{e13e6cc18f554bbbbbbb88953d8c05c4,

title = "Event extraction for systems biology by text mining the literature",

abstract = "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. {\textcopyright} 2010 Elsevier Ltd.",

author = "Sophia Ananiadou and Sampo Pyysalo and Jun'ichi Tsujii and Kell, {Douglas B.}",

note = "Work towards this review was partly supported by the Biotechnology and Biological Sciences Research Council in the context of grants BB/E004431/1 and BB/G53025X/1. We would like to thank Paul Thompson and John McNaught (National Centre for Text Mining, University of Manchester) for their helpful comments and support in producing this manuscript.",

year = "2010",

month = jul,

doi = "10.1016/j.tibtech.2010.04.005",

language = "English",

volume = "28",

pages = "381--390",

journal = "Trends in Biotechnology",

issn = "0167-7799",

publisher = "Elsevier BV",

number = "7",

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T1 - Event extraction for systems biology by text mining the literature

AU - Ananiadou, Sophia

AU - Pyysalo, Sampo

AU - Tsujii, Jun'ichi

AU - Kell, Douglas B.

N1 - Work towards this review was partly supported by the Biotechnology and Biological Sciences Research Council in the context of grants BB/E004431/1 and BB/G53025X/1. We would like to thank Paul Thompson and John McNaught (National Centre for Text Mining, University of Manchester) for their helpful comments and support in producing this manuscript.

PY - 2010/7

Y1 - 2010/7

N2 - 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. © 2010 Elsevier Ltd.

AB - 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. © 2010 Elsevier Ltd.

U2 - 10.1016/j.tibtech.2010.04.005

DO - 10.1016/j.tibtech.2010.04.005

M3 - Article

SN - 0167-7799

VL - 28

SP - 381

EP - 390

JO - Trends in Biotechnology

JF - Trends in Biotechnology

IS - 7

ER -

Event extraction for systems biology by text mining the literature

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