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Oxford University Press, Bioinformatics, 8(33), p. 1205-1209, 2016

DOI: 10.1093/bioinformatics/btw782

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Analyzing user-generated online content for drug discovery: development and use of MedCrawler

Journal article published in 2016 by Andreas Helfenstein, Päivi Tammela ORCID
This paper is available in a repository.
This paper is available in a repository.

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Abstract

Abstract Motivation Ethnopharmacology, or the scientific validation of traditional medicine, is a respected starting point in drug discovery. Home remedies and traditional use of plants are still widespread, also in Western societies. Instead of perusing ancient pharmacopeias, we developed MedCrawler, which we used to analyze blog posts for mentions of home remedies and their applications. This method is free and accessible from the office computer. Results We developed MedCrawler, a data mining tool for analyzing user-generated blog posts aiming to find modern ‘traditional’ medicine or home remedies. It searches user-generated blog posts and analyzes them for correlations between medically relevant terms. We also present examples and show that this method is capable of delivering both scientifically validated uses as well as not so well documented applications, which might serve as a starting point for follow-up research. Availability and Implementation Source code is available on GitHub at {{https://github.com/a-hel/medcrawler}} Supplementary information Supplementary data are available at Bioinformatics online.