Virtual screening for PPAR-gamma ligands using the ISOAK molecular graph kernel and gaussian processes

  • For a virtual screening study, we introduce a combination of machine learning techniques, employing a graph kernel, Gaussian process regression and clustered cross-validation. The aim was to find ligands of peroxisome-proliferator activated receptor gamma (PPAR-y). The receptors in the PPAR family belong to the steroid-thyroid-retinoid superfamily of nuclear receptors and act as transcription factors. They play a role in the regulation of lipid and glucose metabolism in vertebrates and are linked to various human processes and diseases. For this study, we used a dataset of 176 PPAR-y agonists published by Ruecker et al. ...

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Author:Timon Schroeter, Matthias Rupp, Katja Hansen, Klaus-Robert Müller, Gisbert SchneiderORCiDGND
Parent Title (English):Chemistry central journal
Publisher:BioMed Central
Place of publication:London
Document Type:Article
Year of Completion:2009
Date of first Publication:2009/06/05
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Creating Corporation:4th German Conference on Chemoinformatics, Goslar, Germany. 9–11 November 2008
Release Date:2009/08/26
Tag:Gaussian Process; Multiple Kernel; Support Vector Regression; Support Vector Regression Model; Virtual Screening
Issue:Supplement 1, P15
Page Number:2
First Page:1
Last Page:2
© 2009 Schroeter et al; licensee BioMed Central Ltd.
Source:4th German Conference on Chemoinformatics Goslar, Germany. 9–11 November 2008 ; Chemistry Central Journal 2009, 3(Suppl 1):P15 ; doi:10.1186/1752-153X-3-S1-P15 ;
Institutes:Biochemie, Chemie und Pharmazie / Biochemie und Chemie
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 54 Chemie / 540 Chemie und zugeordnete Wissenschaften
Licence (German):License LogoDeutsches Urheberrecht