Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism

In metabolic engineering, mechanistic models require prior metabolism knowledge of the chassis strain, whereas machine learning models need ample training data. Here, the authors combine the mechanistic and machine learning models to improve prediction performance of tryptophan metabolism in baker’s...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Jie Zhang, Søren D. Petersen, Tijana Radivojevic, Andrés Ramirez, Andrés Pérez-Manríquez, Eduardo Abeliuk, Benjamín J. Sánchez, Zak Costello, Yu Chen, Michael J. Fero, Hector Garcia Martin, Jens Nielsen, Jay D. Keasling, Michael K. Jensen
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/12b7d69682c04fc38cfe252ad2aedc1b
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:12b7d69682c04fc38cfe252ad2aedc1b
record_format	dspace
spelling	oai:doaj.org-article:12b7d69682c04fc38cfe252ad2aedc1b2021-12-02T17:27:20ZCombining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism10.1038/s41467-020-17910-12041-1723https://doaj.org/article/12b7d69682c04fc38cfe252ad2aedc1b2020-09-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-17910-1https://doaj.org/toc/2041-1723In metabolic engineering, mechanistic models require prior metabolism knowledge of the chassis strain, whereas machine learning models need ample training data. Here, the authors combine the mechanistic and machine learning models to improve prediction performance of tryptophan metabolism in baker’s yeast.Jie ZhangSøren D. PetersenTijana RadivojevicAndrés RamirezAndrés Pérez-ManríquezEduardo AbeliukBenjamín J. SánchezZak CostelloYu ChenMichael J. FeroHector Garcia MartinJens NielsenJay D. KeaslingMichael K. JensenNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-13 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Jie Zhang Søren D. Petersen Tijana Radivojevic Andrés Ramirez Andrés Pérez-Manríquez Eduardo Abeliuk Benjamín J. Sánchez Zak Costello Yu Chen Michael J. Fero Hector Garcia Martin Jens Nielsen Jay D. Keasling Michael K. Jensen Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism
description	In metabolic engineering, mechanistic models require prior metabolism knowledge of the chassis strain, whereas machine learning models need ample training data. Here, the authors combine the mechanistic and machine learning models to improve prediction performance of tryptophan metabolism in baker’s yeast.
format	article
author	Jie Zhang Søren D. Petersen Tijana Radivojevic Andrés Ramirez Andrés Pérez-Manríquez Eduardo Abeliuk Benjamín J. Sánchez Zak Costello Yu Chen Michael J. Fero Hector Garcia Martin Jens Nielsen Jay D. Keasling Michael K. Jensen
author_facet	Jie Zhang Søren D. Petersen Tijana Radivojevic Andrés Ramirez Andrés Pérez-Manríquez Eduardo Abeliuk Benjamín J. Sánchez Zak Costello Yu Chen Michael J. Fero Hector Garcia Martin Jens Nielsen Jay D. Keasling Michael K. Jensen
author_sort	Jie Zhang
title	Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism
title_short	Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism
title_full	Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism
title_fullStr	Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism
title_full_unstemmed	Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism
title_sort	combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/12b7d69682c04fc38cfe252ad2aedc1b
work_keys_str_mv	AT jiezhang combiningmechanisticandmachinelearningmodelsforpredictiveengineeringandoptimizationoftryptophanmetabolism AT sørendpetersen combiningmechanisticandmachinelearningmodelsforpredictiveengineeringandoptimizationoftryptophanmetabolism AT tijanaradivojevic combiningmechanisticandmachinelearningmodelsforpredictiveengineeringandoptimizationoftryptophanmetabolism AT andresramirez combiningmechanisticandmachinelearningmodelsforpredictiveengineeringandoptimizationoftryptophanmetabolism AT andresperezmanriquez combiningmechanisticandmachinelearningmodelsforpredictiveengineeringandoptimizationoftryptophanmetabolism AT eduardoabeliuk combiningmechanisticandmachinelearningmodelsforpredictiveengineeringandoptimizationoftryptophanmetabolism AT benjaminjsanchez combiningmechanisticandmachinelearningmodelsforpredictiveengineeringandoptimizationoftryptophanmetabolism AT zakcostello combiningmechanisticandmachinelearningmodelsforpredictiveengineeringandoptimizationoftryptophanmetabolism AT yuchen combiningmechanisticandmachinelearningmodelsforpredictiveengineeringandoptimizationoftryptophanmetabolism AT michaeljfero combiningmechanisticandmachinelearningmodelsforpredictiveengineeringandoptimizationoftryptophanmetabolism AT hectorgarciamartin combiningmechanisticandmachinelearningmodelsforpredictiveengineeringandoptimizationoftryptophanmetabolism AT jensnielsen combiningmechanisticandmachinelearningmodelsforpredictiveengineeringandoptimizationoftryptophanmetabolism AT jaydkeasling combiningmechanisticandmachinelearningmodelsforpredictiveengineeringandoptimizationoftryptophanmetabolism AT michaelkjensen combiningmechanisticandmachinelearningmodelsforpredictiveengineeringandoptimizationoftryptophanmetabolism
_version_	1718380774983467008

Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism

Ejemplares similares