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Methods Mol Biol. 2007;401:3-21. doi: 10.1007/978-1-59745-520-6_1.

Managing knowledge in neuroscience.

Author information

1
Yale Center for Medical Informatics and Department of Neurobiology, Yale University School of Medicine, New Haven, CT, USA.

Abstract

Processing text from scientific literature has become a necessity due to the burgeoning amounts of information that are fast becoming available, stemming from advances in electronic information technology. We created a program, NeuroText ( http://senselab.med.yale.edu/textmine/neurotext.pl ), designed specifically to extract information relevant to neuroscience-specific databases, NeuronDB and CellPropDB ( http://senselab.med.yale.edu/senselab/ ), housed at the Yale University School of Medicine. NeuroText extracts relevant information from the Neuroscience literature in a two-step process: each step parses text at different levels of granularity. NeuroText uses an expert-mediated knowledge base and combines the techniques of indexing, contextual parsing, semantic and lexical parsing, and supervised and non-supervised learning to extract information. The constrains, metadata elements, and rules for information extraction are stored in the knowledge base. NeuroText was created as a pilot project to process 3 years of publications in Journal of Neuroscience and was subsequently tested for 40,000 PubMed abstracts. We also present here a template to create domain non-specific knowledge base that when linked to a text-processing tool like NeuroText can be used to extract knowledge in other fields of research.

PMID:
18368357
DOI:
10.1007/978-1-59745-520-6_1
[Indexed for MEDLINE]
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