High-throughput brain activity mapping and machine learning as a foundation for systems neuropharmacology

A major goal in neuropharmacology is to develop new tools to effectively test the therapeutic potential of pharmacological agents to treat neurological and psychiatric conditions. Here, authors present an in vivo drug screening system that generates large-scale brain activity maps to be used with ma...

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Autores principales:	Xudong Lin, Xin Duan, Claire Jacobs, Jeremy Ullmann, Chung-Yuen Chan, Siya Chen, Shuk-Han Cheng, Wen-Ning Zhao, Annapurna Poduri, Xin Wang, Stephen J. Haggarty, Peng Shi
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/709f8352b59f4f82a66f22e89e4f510e
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spelling	oai:doaj.org-article:709f8352b59f4f82a66f22e89e4f510e2021-12-02T14:39:47ZHigh-throughput brain activity mapping and machine learning as a foundation for systems neuropharmacology10.1038/s41467-018-07289-52041-1723https://doaj.org/article/709f8352b59f4f82a66f22e89e4f510e2018-12-01T00:00:00Zhttps://doi.org/10.1038/s41467-018-07289-5https://doaj.org/toc/2041-1723A major goal in neuropharmacology is to develop new tools to effectively test the therapeutic potential of pharmacological agents to treat neurological and psychiatric conditions. Here, authors present an in vivo drug screening system that generates large-scale brain activity maps to be used with machine learning to predict the therapeutic potential of clinically relevant drug leads.Xudong LinXin DuanClaire JacobsJeremy UllmannChung-Yuen ChanSiya ChenShuk-Han ChengWen-Ning ZhaoAnnapurna PoduriXin WangStephen J. HaggartyPeng ShiNature PortfolioarticleScienceQENNature Communications, Vol 9, Iss 1, Pp 1-12 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Xudong Lin Xin Duan Claire Jacobs Jeremy Ullmann Chung-Yuen Chan Siya Chen Shuk-Han Cheng Wen-Ning Zhao Annapurna Poduri Xin Wang Stephen J. Haggarty Peng Shi High-throughput brain activity mapping and machine learning as a foundation for systems neuropharmacology
description	A major goal in neuropharmacology is to develop new tools to effectively test the therapeutic potential of pharmacological agents to treat neurological and psychiatric conditions. Here, authors present an in vivo drug screening system that generates large-scale brain activity maps to be used with machine learning to predict the therapeutic potential of clinically relevant drug leads.
format	article
author	Xudong Lin Xin Duan Claire Jacobs Jeremy Ullmann Chung-Yuen Chan Siya Chen Shuk-Han Cheng Wen-Ning Zhao Annapurna Poduri Xin Wang Stephen J. Haggarty Peng Shi
author_facet	Xudong Lin Xin Duan Claire Jacobs Jeremy Ullmann Chung-Yuen Chan Siya Chen Shuk-Han Cheng Wen-Ning Zhao Annapurna Poduri Xin Wang Stephen J. Haggarty Peng Shi
author_sort	Xudong Lin
title	High-throughput brain activity mapping and machine learning as a foundation for systems neuropharmacology
title_short	High-throughput brain activity mapping and machine learning as a foundation for systems neuropharmacology
title_full	High-throughput brain activity mapping and machine learning as a foundation for systems neuropharmacology
title_fullStr	High-throughput brain activity mapping and machine learning as a foundation for systems neuropharmacology
title_full_unstemmed	High-throughput brain activity mapping and machine learning as a foundation for systems neuropharmacology
title_sort	high-throughput brain activity mapping and machine learning as a foundation for systems neuropharmacology
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/709f8352b59f4f82a66f22e89e4f510e
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High-throughput brain activity mapping and machine learning as a foundation for systems neuropharmacology

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