Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade

Michelle Przedborski et al. report an integrative systems biology and machine learning method for predicting cancer patient responses to immunotherapy treatment. Using their method, they identify several new drug combinations that could potentially improve treatment protocols for immunotherapy.

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Detalles Bibliográficos
Autores principales:	Michelle Przedborski, Munisha Smalley, Saravanan Thiyagarajan, Aaron Goldman, Mohammad Kohandel
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/44e3f66755784e83bdb6e51e9bad3437
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spelling	oai:doaj.org-article:44e3f66755784e83bdb6e51e9bad34372021-12-02T16:09:42ZSystems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade10.1038/s42003-021-02393-72399-3642https://doaj.org/article/44e3f66755784e83bdb6e51e9bad34372021-07-01T00:00:00Zhttps://doi.org/10.1038/s42003-021-02393-7https://doaj.org/toc/2399-3642Michelle Przedborski et al. report an integrative systems biology and machine learning method for predicting cancer patient responses to immunotherapy treatment. Using their method, they identify several new drug combinations that could potentially improve treatment protocols for immunotherapy.Michelle PrzedborskiMunisha SmalleySaravanan ThiyagarajanAaron GoldmanMohammad KohandelNature PortfolioarticleBiology (General)QH301-705.5ENCommunications Biology, Vol 4, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Michelle Przedborski Munisha Smalley Saravanan Thiyagarajan Aaron Goldman Mohammad Kohandel Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade
description	Michelle Przedborski et al. report an integrative systems biology and machine learning method for predicting cancer patient responses to immunotherapy treatment. Using their method, they identify several new drug combinations that could potentially improve treatment protocols for immunotherapy.
format	article
author	Michelle Przedborski Munisha Smalley Saravanan Thiyagarajan Aaron Goldman Mohammad Kohandel
author_facet	Michelle Przedborski Munisha Smalley Saravanan Thiyagarajan Aaron Goldman Mohammad Kohandel
author_sort	Michelle Przedborski
title	Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade
title_short	Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade
title_full	Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade
title_fullStr	Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade
title_full_unstemmed	Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade
title_sort	systems biology informed neural networks (sbinn) predict response and novel combinations for pd-1 checkpoint blockade
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/44e3f66755784e83bdb6e51e9bad3437
work_keys_str_mv	AT michelleprzedborski systemsbiologyinformedneuralnetworkssbinnpredictresponseandnovelcombinationsforpd1checkpointblockade AT munishasmalley systemsbiologyinformedneuralnetworkssbinnpredictresponseandnovelcombinationsforpd1checkpointblockade AT saravananthiyagarajan systemsbiologyinformedneuralnetworkssbinnpredictresponseandnovelcombinationsforpd1checkpointblockade AT aarongoldman systemsbiologyinformedneuralnetworkssbinnpredictresponseandnovelcombinationsforpd1checkpointblockade AT mohammadkohandel systemsbiologyinformedneuralnetworkssbinnpredictresponseandnovelcombinationsforpd1checkpointblockade
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Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade

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