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Text mining resources for the life sciences

delete2016-11-21
delete34
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OA
AI
P
Piotr Przybyła
M
Matthew Shardlow *
S
Sophie Aubin
R
Robert Bossy
R
Richard Eckart de Castilho
S
Stelios Piperidis
J
John McNaught
S
Sophia Ananiadou
DOI:10.1093/database/baw145delete
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Abstract

Abstract

En 中文
Text mining is a powerful technology for quickly distilling key information from vast quantities of biomedical literature. However, to harness this power the researcher must be well versed in the availability, suitability, adaptability, interoperability and comparative accuracy of current text mining resources. In this survey, we give an overview of the text mining resources that exist in the life sciences to help researchers, especially those employed in biocuration, to engage with text mining in their own work. We categorize the various resources under three sections: Content Discovery looks at where and how to find biomedical publications for text mining; Knowledge Encoding describes the formats used to represent the different levels of information associated with content that enable text mining, including those formats used to carry such information between processes; Tools and Services gives an overview of workflow management systems that can be used to rapidly configure and compare domain-and task-specific processes, via access to a wide range of pre-built tools. We also provide links to relevant repositories in each section to enable the reader to find resources relevant to their own area of interest. Throughout this work we give a special focus to resources that are interoperable-those that have the crucial ability to share information, enabling smooth integration and reusability.
Keywords:
WEB SERVICES
ONTOLOGY
ANNOTATION
SYSTEM
TOOL
RECOGNITION
INTEGRATION
FRAMEWORK
STANDARD
DESIGN
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

D
Database-The Journal of Biological Databases and Curation
IF:
3.6
Papers:
1.8K
Citations:
6.1K

Organization

I
INRAE
Scholars:
4.3W
Papers: 3.1W
Citations: 105
U
Universite Paris Saclay
Scholars:
7.3W
Papers: 5.3W
Citations: 540
U
University of Manchester
Scholars:
5.7W
Papers: 5.3W
Citations: 7.4W
T
Technical University of Darmstadt
Scholars:
1.3W
Papers: 10.0K
Citations: 1.2W
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Cited Papers

Cited Papers

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BioCatalogue: a universal catalogue of web services for the life sciences
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Text mining for the biocuration workflow
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err65
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errHirschman, Lynette; Burns, Gully A. P. C.; Krallinger, Martin; Arighi, Cecilia; Cohen, K. Bretonnel; Valencia, Alfonso; Wu, Cathy H.; Chatr-Aryamontri, Andrew; Dowell, Karen G.; Huala, Eva; Lourenco, Analia; Nash, Robert; Veuthey, Anne-Lise; Wiegers, Thomas; Winter, Andrew G.
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Legal aspects of text mining
err2014-04-01
err34
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errTruyens, Maarten; Van Eecke, Patrick
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