Author

B. J. Sanchez

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Organism:bacteria (other)· 1 Research Focus:benchmarking· 1 Research Focus:drug response / drug discovery· 1 Approach:genetic perturbation / CRISPR· 1 Approach:machine learning (classical)· 1 Approach:mechanistic / dynamical model· 1 Research Focus:metabolism & bioenergetics· 1 Assay:metabolomics· 1

Frequent Co-Authors

A. Perez· 1 shared A. Ramirez· 1 shared A. Toftgaard Nielsen· 1 shared B. K. Lisowska· 1 shared D. J. Leak· 1 shared E. Abeliuk· 1 shared H. G. Martin· 1 shared J. B. Nielsen· 1 shared

Activity by Year

2019-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperBioengineering

A. Perez

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2 papers

Recent·Most cited

Genome-scale metabolic modelling of P. thermoglucosidasius NCIMB 11955 reveals metabolic bottlenecks in anaerobic metabolism.

V. Mol, M. Bennett, B. J. Sanchez, B. K. Lisowska, M. J. Herrgard, A. Toftgaard Nielsen, D. J. Leak, N. Sonnenschein

This paper develops a genome-scale metabolic model for P. thermoglucosidasius to identify metabolic bottlenecks and guide metabolic engineering.

bioRxiv · Feb 1, 2021Microbiology

Predictive engineering and optimization of tryptophan metabolism in yeast through a combination of mechanistic and machine learning models

J. Zhang, S. D. Petersen, T. Radivojevic, A. Ramirez, A. Perez, E. Abeliuk, B. J. Sanchez, Z. Costello, Y. Chen, M. Fero, H. G. Martin, J. B. Nielsen, J. D. Keasling, M. K. Jensen

This study combines mechanistic and machine learning models to optimize tryptophan metabolism in yeast, achieving a 106% increase in tryptophan accumulation through predictive engineering.

bioRxiv · Nov 29, 2019 · PreprintBioengineering