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Mit semantischem Text Mining von biologischen Netzwerken zum Börsenkurs.

BioSpektrum 18, 333-335 (2012)
Open Access Green as soon as Postprint is submitted to ZB.
Humans are unable to catch knowledge in the structured form of data - base tables but are strong in intuitive understanding by reading free text. To cope with the volume, search for alternatives to explore the biological knowledge buried in the literature is bare necessity. We have employed semantic text mining as an essential tool for the systematic exploration of publications and show that these methods can be applied in many other areas that deal with large amounts of textual information.
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Publication type Article: Journal article
Document type Scientific Article
Reviewing status