Accurate prediction of in vivo protein abundances by coupling constraint-based modelling and machine learning-Reference-Cited by-同舟云学术

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Accurate prediction of in vivo protein abundances by coupling constraint-based modelling and machine learning

Published:2023-11 Issue: Volume:80 Page:184-192
ISSN:1096-7176
Container-title:Metabolic Engineering
language:en
Short-container-title:Metabolic Engineering

Author:

Moura Ferreira Maurício Alexander de^ORCID,Wendering Philipp,Arend Marius,Batista da Silveira Wendel,Nikoloski Zoran^ORCID

Funder

Horizon 2020

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Max-Planck-Gesellschaft

Universität Potsdam

Publisher

Elsevier BV

Subject

Applied Microbiology and Biotechnology,Bioengineering,Biotechnology

Reference52 articles.

1. Prediction of microbial growth rate versus biomass yield by a metabolic network with kinetic parameters;Adadi;PLoS Comput. Biol.,2012

2. Proteome regulation patterns determine Escherichia coli wild-type and mutant phenotypes;Alter;mSystems,2021

3. Gene Ontology: tool for the unification of biology;Ashburner;Nat. Genet.,2000

4. Intracellular crowding defines the mode and sequence of substrate uptake by Escherichia coli and constrains its metabolic activity;Beg;Proc. Natl. Acad. Sci. U.S.A.,2007

5. Automatic construction of metabolic models with enzyme constraints;Bekiaris;BMC Bioinf.,2020

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Protein constraints in genome‐scale metabolic models: Data integration, parameter estimation, and prediction of metabolic phenotypes;Biotechnology and Bioengineering;2024-01-04

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