Author

Z. Costello

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:yeast· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

J. D. Keasling· 2 shared A. Mukhopadhyay· 1 shared A. Perez· 1 shared A. Ramirez· 1 shared B. J. Sanchez· 1 shared C. A. Barcelos· 1 shared D. Banerjee· 1 shared D. Tanjore· 1 shared

Activity by Year

2019-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersMicrobiology

J. D. Keasling

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2 papers

Recent·Most cited

Population dynamics analysis of Saccharomyces cerevisiae deletion library during fed-batch cultivation using Bar-seq

M. Wehrs, M. Thompson, D. Banerjee, J.-P. Prahl, C. A. Barcelos, J. Moon, N. M. Morella, Z. Costello, J. D. Keasling, P. M. Shih, D. Tanjore, A. Mukhopadhyay

The paper uses Bar-seq to analyze population dynamics of a yeast deletion library during fed-batch cultivation, identifying genes associated with stress responses in industrial fermentation.

bioRxiv · Apr 27, 2020Microbiology

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