Discovery of Novel Molecular Frameworks of Farnesoid X Receptor Modulators by Ensemble Machine Learning

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Invited for this month's cover picture is the group of Prof. Dr. Gisbert Schneider from the Swiss Federal Institute of Technology (ETH) Zurich (Switzerland). The cover picture illustrates the application of machine‐learning methods to expand the chemical space of farnesoid X receptor (FXR)‐targ...

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Autores principales: Merk, Daniel, Grisoni, Francesca, Schaller, Kay, Friedrich, Lukas, Schneider, Gisbert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Cover Profile
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6317921/
https://www.ncbi.nlm.nih.gov/pubmed/30622876
http://dx.doi.org/10.1002/open.201800270
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author Merk, Daniel
Grisoni, Francesca
Schaller, Kay
Friedrich, Lukas
Schneider, Gisbert
author_facet Merk, Daniel
Grisoni, Francesca
Schaller, Kay
Friedrich, Lukas
Schneider, Gisbert
author_sort Merk, Daniel
collection PubMed
description Invited for this month's cover picture is the group of Prof. Dr. Gisbert Schneider from the Swiss Federal Institute of Technology (ETH) Zurich (Switzerland). The cover picture illustrates the application of machine‐learning methods to expand the chemical space of farnesoid X receptor (FXR)‐targeting small molecules, by employing an ensemble of three complementary machine‐learning approaches (counter‐propagation artificial neural network, k‐nearest neighbor learner, and three‐dimensional pharmacophore model). Read the full text of their Full Paper at 10.1002/open.201800156.
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spelling pubmed-63179212019-01-08 Discovery of Novel Molecular Frameworks of Farnesoid X Receptor Modulators by Ensemble Machine Learning Merk, Daniel Grisoni, Francesca Schaller, Kay Friedrich, Lukas Schneider, Gisbert ChemistryOpen Cover Profile Invited for this month's cover picture is the group of Prof. Dr. Gisbert Schneider from the Swiss Federal Institute of Technology (ETH) Zurich (Switzerland). The cover picture illustrates the application of machine‐learning methods to expand the chemical space of farnesoid X receptor (FXR)‐targeting small molecules, by employing an ensemble of three complementary machine‐learning approaches (counter‐propagation artificial neural network, k‐nearest neighbor learner, and three‐dimensional pharmacophore model). Read the full text of their Full Paper at 10.1002/open.201800156. John Wiley and Sons Inc. 2018-12-06 /pmc/articles/PMC6317921/ /pubmed/30622876 http://dx.doi.org/10.1002/open.201800270 Text en © 2019 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim
spellingShingle Cover Profile
Merk, Daniel
Grisoni, Francesca
Schaller, Kay
Friedrich, Lukas
Schneider, Gisbert
Discovery of Novel Molecular Frameworks of Farnesoid X Receptor Modulators by Ensemble Machine Learning
title Discovery of Novel Molecular Frameworks of Farnesoid X Receptor Modulators by Ensemble Machine Learning
title_full Discovery of Novel Molecular Frameworks of Farnesoid X Receptor Modulators by Ensemble Machine Learning
title_fullStr Discovery of Novel Molecular Frameworks of Farnesoid X Receptor Modulators by Ensemble Machine Learning
title_full_unstemmed Discovery of Novel Molecular Frameworks of Farnesoid X Receptor Modulators by Ensemble Machine Learning
title_short Discovery of Novel Molecular Frameworks of Farnesoid X Receptor Modulators by Ensemble Machine Learning
title_sort discovery of novel molecular frameworks of farnesoid x receptor modulators by ensemble machine learning
topic Cover Profile
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6317921/
https://www.ncbi.nlm.nih.gov/pubmed/30622876
http://dx.doi.org/10.1002/open.201800270
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