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BioRAT: A Search Engine and Information Extraction Tool for Biological Research (RRID:SCR_013452)Copy Citation Copied
URL: http://bioinf.cs.ucl.ac.uk/software_downloads/biorat/
Proper Citation: BioRAT: A Search Engine and Information Extraction Tool for Biological Research (RRID:SCR_013452)
Description: BioRAT is a virtual research assistant, which will find research papers for users, read them, and tell users the key facts it finds. It is part of an ongoing research project, and so is NOT a highly-polished, well-supported, fully-documented system that we might dream of. With suitable cajoling, it will let users find and download biological research papers, principally through PubMed. It will let them specify patterns of interesting words / phrases, and use these to read papers. Lastly, it will put the results into a variety of useful formats, including XML and HTML. A large and growing amount of information is published every year in scientific journals. In the biomedical field, there are thousands of journals, each publishing many issues annually, any one of which could contain information that is relevant to a researcher. However, no one has time to read every paper. One solution is to use a software tool to search through publications to identify important results in response to the users' queries. BioRAT is such a tool. BioRAT is a new information extraction (IE) tool, specifically designed to perform biomedical IE, and which is able to locate and analyse both abstracts and full-length papers. BioRAT is a Biological Research Assistant for Text mining, and incorporates a document search ability with domain-specific IE. Overall, BioRAT recalled 20.31% of the target facts from the abstracts with 55.07% precision, and achieved 43.6% recall with 51.25% precision on full-length papers. Sponsors: The ongoing project is now funded by the BBSRC.
Synonyms: BioRAT
Resource Type: software resource, text-mining software, software application, data analysis software, data processing software, text extraction software
Keywords: facts, biological, document, paper, research, scientific literature databases and services, journal
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Data set from Kravitz, Owen and Kretizer's 2012 paper "Optogenetic identification of striatal projection neuron subtypes during in vivo recordings."
