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Text mining resources for the life sciences
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 minin...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5199186/ https://www.ncbi.nlm.nih.gov/pubmed/27888231 http://dx.doi.org/10.1093/database/baw145 |
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author | Przybyła, Piotr Shardlow, Matthew Aubin, Sophie Bossy, Robert Eckart de Castilho, Richard Piperidis, Stelios McNaught, John Ananiadou, Sophia |
author_facet | Przybyła, Piotr Shardlow, Matthew Aubin, Sophie Bossy, Robert Eckart de Castilho, Richard Piperidis, Stelios McNaught, John Ananiadou, Sophia |
author_sort | Przybyła, Piotr |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5199186 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-51991862017-01-06 Text mining resources for the life sciences Przybyła, Piotr Shardlow, Matthew Aubin, Sophie Bossy, Robert Eckart de Castilho, Richard Piperidis, Stelios McNaught, John Ananiadou, Sophia Database (Oxford) Review 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. Oxford University Press 2016-10-25 /pmc/articles/PMC5199186/ /pubmed/27888231 http://dx.doi.org/10.1093/database/baw145 Text en © The Author(s) 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Przybyła, Piotr Shardlow, Matthew Aubin, Sophie Bossy, Robert Eckart de Castilho, Richard Piperidis, Stelios McNaught, John Ananiadou, Sophia Text mining resources for the life sciences |
title | Text mining resources for the life sciences |
title_full | Text mining resources for the life sciences |
title_fullStr | Text mining resources for the life sciences |
title_full_unstemmed | Text mining resources for the life sciences |
title_short | Text mining resources for the life sciences |
title_sort | text mining resources for the life sciences |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5199186/ https://www.ncbi.nlm.nih.gov/pubmed/27888231 http://dx.doi.org/10.1093/database/baw145 |
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