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Automated QuantMap for rapid quantitative molecular network topology analysis
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.ORCID iD: 0000-0002-8083-2864
2013 (English)In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 29, no 18, 2369-2370 p.Article in journal (Refereed) Published
Abstract [en]

SUMMARY:

The previously disclosed QuantMap method for grouping chemicals by biological activity used online services for much of the data gathering and some of the numerical analysis. The present work attempts to streamline this process by using local copies of the databases and in-house analysis. Using computational methods similar or identical to those used in the previous work, a qualitatively equivalent result was found in just a few seconds on the same dataset (collection of 18 drugs). We use the user-friendly Galaxy framework to enable users to analyze their own datasets. Hopefully, this will make the QuantMap method more practical and accessible and help achieve its goals to provide substantial assistance to drug repositioning, pharmacology evaluation and toxicology risk assessment.

AVAILABILITY:

http://galaxy.predpharmtox.org

CONTACT:

mats.gustafsson@medsci.uu.se or ola.spjuth@farmbio.uu.se

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

Place, publisher, year, edition, pages
2013. Vol. 29, no 18, 2369-2370 p.
National Category
Bioinformatics and Systems Biology
Research subject
Bioinformatics
Identifiers
URN: urn:nbn:se:uu:diva-204704DOI: 10.1093/bioinformatics/btt390ISI: 000323943200024PubMedID: 23828784OAI: oai:DiVA.org:uu-204704DiVA: diva2:639713
Funder
eSSENCE - An eScience CollaborationSwedish Research Council, 2011-6129
Available from: 2013-08-08 Created: 2013-08-08 Last updated: 2017-12-06Bibliographically approved

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