Exploring use of unsupervised clustering to associate signaling profiles of GPCR ligands to clinical response

Identifying ligands which activate the specific effectors driving particular in vivo drug effects remains challenging. Here, the authors apply unsupervised clustering of pharmacodynamic parameters to classify GPCR ligands into different categories with similar signaling profiles and shared frequency...

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Autores principales:	Besma Benredjem, Jonathan Gallion, Dennis Pelletier, Paul Dallaire, Johanie Charbonneau, Darren Cawkill, Karim Nagi, Mark Gosink, Viktoryia Lukasheva, Stephen Jenkinson, Yong Ren, Christopher Somps, Brigitte Murat, Emma Van Der Westhuizen, Christian Le Gouill, Olivier Lichtarge, Anne Schmidt, Michel Bouvier, Graciela Pineyro
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/c0db3f1cf110426bbd5f35d40fd3681b
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spelling	oai:doaj.org-article:c0db3f1cf110426bbd5f35d40fd3681b2021-12-02T16:57:41ZExploring use of unsupervised clustering to associate signaling profiles of GPCR ligands to clinical response10.1038/s41467-019-11875-62041-1723https://doaj.org/article/c0db3f1cf110426bbd5f35d40fd3681b2019-09-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-11875-6https://doaj.org/toc/2041-1723Identifying ligands which activate the specific effectors driving particular in vivo drug effects remains challenging. Here, the authors apply unsupervised clustering of pharmacodynamic parameters to classify GPCR ligands into different categories with similar signaling profiles and shared frequency of report of side effects.Besma BenredjemJonathan GallionDennis PelletierPaul DallaireJohanie CharbonneauDarren CawkillKarim NagiMark GosinkViktoryia LukashevaStephen JenkinsonYong RenChristopher SompsBrigitte MuratEmma Van Der WesthuizenChristian Le GouillOlivier LichtargeAnne SchmidtMichel BouvierGraciela PineyroNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-15 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Besma Benredjem Jonathan Gallion Dennis Pelletier Paul Dallaire Johanie Charbonneau Darren Cawkill Karim Nagi Mark Gosink Viktoryia Lukasheva Stephen Jenkinson Yong Ren Christopher Somps Brigitte Murat Emma Van Der Westhuizen Christian Le Gouill Olivier Lichtarge Anne Schmidt Michel Bouvier Graciela Pineyro Exploring use of unsupervised clustering to associate signaling profiles of GPCR ligands to clinical response
description	Identifying ligands which activate the specific effectors driving particular in vivo drug effects remains challenging. Here, the authors apply unsupervised clustering of pharmacodynamic parameters to classify GPCR ligands into different categories with similar signaling profiles and shared frequency of report of side effects.
format	article
author	Besma Benredjem Jonathan Gallion Dennis Pelletier Paul Dallaire Johanie Charbonneau Darren Cawkill Karim Nagi Mark Gosink Viktoryia Lukasheva Stephen Jenkinson Yong Ren Christopher Somps Brigitte Murat Emma Van Der Westhuizen Christian Le Gouill Olivier Lichtarge Anne Schmidt Michel Bouvier Graciela Pineyro
author_facet	Besma Benredjem Jonathan Gallion Dennis Pelletier Paul Dallaire Johanie Charbonneau Darren Cawkill Karim Nagi Mark Gosink Viktoryia Lukasheva Stephen Jenkinson Yong Ren Christopher Somps Brigitte Murat Emma Van Der Westhuizen Christian Le Gouill Olivier Lichtarge Anne Schmidt Michel Bouvier Graciela Pineyro
author_sort	Besma Benredjem
title	Exploring use of unsupervised clustering to associate signaling profiles of GPCR ligands to clinical response
title_short	Exploring use of unsupervised clustering to associate signaling profiles of GPCR ligands to clinical response
title_full	Exploring use of unsupervised clustering to associate signaling profiles of GPCR ligands to clinical response
title_fullStr	Exploring use of unsupervised clustering to associate signaling profiles of GPCR ligands to clinical response
title_full_unstemmed	Exploring use of unsupervised clustering to associate signaling profiles of GPCR ligands to clinical response
title_sort	exploring use of unsupervised clustering to associate signaling profiles of gpcr ligands to clinical response
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/c0db3f1cf110426bbd5f35d40fd3681b
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Exploring use of unsupervised clustering to associate signaling profiles of GPCR ligands to clinical response

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