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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.
Databases, Factual, workflow, Bioinformatics, growth, text mining resources, researchers, integration, interoperability, text mining, Review, system, linguistic annotation, ResearchInstitutes_Networks_Beacons/manchester_institute_of_biotechnology; name=Manchester Institute of Biotechnology, Manchester Institute of Biotechnology, Data Mining, Humans, ontology, linguistic annotation;web services;ontology;system;integration;growth;tool;implementation;researchers;workflow, implementation, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], knowledge encoding, content discovery, biocuration, 006, tool, annotation formats, web services, Bio-informatique, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], repositories, aggregators
Databases, Factual, workflow, Bioinformatics, growth, text mining resources, researchers, integration, interoperability, text mining, Review, system, linguistic annotation, ResearchInstitutes_Networks_Beacons/manchester_institute_of_biotechnology; name=Manchester Institute of Biotechnology, Manchester Institute of Biotechnology, Data Mining, Humans, ontology, linguistic annotation;web services;ontology;system;integration;growth;tool;implementation;researchers;workflow, implementation, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], knowledge encoding, content discovery, biocuration, 006, tool, annotation formats, web services, Bio-informatique, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], repositories, aggregators
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 43 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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| downloads | 5 |

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