Skip to main content
bioRxiv

Active and machine learning-based approaches to rapidly enhance microbial chemical production

Publication ,  Preprint
Kumar, P; Adamczyk, P; Zhang, X; Andrade, RB; Romero, P; Ramanathan, P; Reed, J
2020

Duke Scholars

DOI

Publication Date

2020
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Kumar, P., Adamczyk, P., Zhang, X., Andrade, R. B., Romero, P., Ramanathan, P., & Reed, J. (2020). Active and machine learning-based approaches to rapidly enhance microbial chemical production. bioRxiv. https://doi.org/10.1101/2020.12.01.406439
Kumar, Prashant, Paul Adamczyk, Xiaolin Zhang, Ramon Bonela Andrade, Philip Romero, Parameswaran Ramanathan, and Jennifer Reed. “Active and machine learning-based approaches to rapidly enhance microbial chemical production.” BioRxiv, 2020. https://doi.org/10.1101/2020.12.01.406439.
Kumar P, Adamczyk P, Zhang X, Andrade RB, Romero P, Ramanathan P, et al. Active and machine learning-based approaches to rapidly enhance microbial chemical production. bioRxiv. 2020.
Kumar, Prashant, et al. “Active and machine learning-based approaches to rapidly enhance microbial chemical production.” BioRxiv, 2020. Epmc, doi:10.1101/2020.12.01.406439.
Kumar P, Adamczyk P, Zhang X, Andrade RB, Romero P, Ramanathan P, Reed J. Active and machine learning-based approaches to rapidly enhance microbial chemical production. bioRxiv. 2020.

DOI

Publication Date

2020