Mapping of biomedical text to concepts of lexicons, terminologies, and ontologies.
Concept mapping is a fundamental task in biomedical text mining in which textual mentions of concepts of interest are annotated with specific entries of lexicons, terminologies, ontologies, or databases representing these concepts. Though there has been a significant amount of research, there are still a limited number of practical, publicly available tools for concept mapping of biomedical text specified by the user as an independent task. In this chapter, several tools that can automatically map biomedical text to concepts from a wide range of terminological resources are presented, followed by those that can map to more restricted sets of these resources. This presentation is intended to serve as a guide to researchers without a background in biomedical concept mapping of text for the selection of an appropriate tool based on usability, scalability, configurability, balance between precision and recall, and the desired set of terminological resources with which to annotate the text. Only with effective automatic concept-mapping tools will systems be able to scalably analyze the biomedical literature and other large sets of documents as a fundamental part of more complex text-mining tasks such as information extraction and hypothesis evaluation and generation.
Computational Bioscience program, School of Medicine, University of Colorado Anschutz Medical Campus, 12801 E. 17th Ave., RC1S L18-6103, Aurora, CO, 80045-0511, USA, mike.bada@ucdenver.edu.
Michael
M
Bada
D064229:Biological Ontologies; D003210:Concept Formation; D057225:Data Mining / Q000379:methods*; D009626:Terminology as Topic