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

Andreas Helfenstein; Päivi Tammela

doi:10.1093/bioinformatics/btw782

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

Andreas Helfenstein, Päivi Tammela

Research output: Contribution to journal › Article › Scientific › peer-review

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.

Original language	English
Journal	Bioinformatics
Volume	33
Issue number	8
Pages (from-to)	1205-1209
Number of pages	5
ISSN	1367-4803
DOIs	https://doi.org/10.1093/bioinformatics/btw782
Publication status	Published - 15 Apr 2017
MoE publication type	A1 Journal article-refereed

Fields of Science

1182 Biochemistry, cell and molecular biology
220 Industrial biotechnology

Access to Document

10.1093/bioinformatics/btw782

Helfenstein_2017_Bioinformatics_AcceptedAccepted author manuscript, 1.5 MB

Phenotypic biosensor-based HTS and mode of action analysis by metabolomics and transcriptomics for enhancing antimicrobial drug discovery against Gram-negative bacteria
Tammela, P.
01/09/2014 → 31/08/2019
Project: Research project

Cite this

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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.",

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AB - 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.

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

Abstract

Fields of Science

Access to Document

Projects

Phenotypic biosensor-based HTS and mode of action analysis by metabolomics and transcriptomics for enhancing antimicrobial drug discovery against Gram-negative bacteria

Cite this