کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10885762 | 1079902 | 2016 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Application of an automated natural language processing (NLP) workflow to enable federated search of external biomedical content in drug discovery and development
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موضوعات مرتبط
علوم زیستی و بیوفناوری
بیوشیمی، ژنتیک و زیست شناسی مولکولی
بیوتکنولوژی یا زیستفناوری
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چکیده انگلیسی
External content sources such as MEDLINE®, National Institutes of Health (NIH) grants and conference websites provide access to the latest breaking biomedical information, which can inform pharmaceutical and biotechnology company pipeline decisions. The value of the sites for industry, however, is limited by the use of the public internet, the limited synonyms, the rarity of batch searching capability and the disconnected nature of the sites. Fortunately, many sites now offer their content for download and we have developed an automated internal workflow that uses text mining and tailored ontologies for programmatic search and knowledge extraction. We believe such an efficient and secure approach provides a competitive advantage to companies needing access to the latest information for a range of use cases and complements manually curated commercial sources.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Drug Discovery Today - Volume 21, Issue 5, May 2016, Pages 826-835
Journal: Drug Discovery Today - Volume 21, Issue 5, May 2016, Pages 826-835
نویسندگان
Robin McEntire, Debbie Szalkowski, James Butler, Michelle S. Kuo, Meiping Chang, Man Chang, Darren Freeman, Sarah McQuay, Jagruti Patel, Michael McGlashen, Wendy D. Cornell, Jinghai James Xu,