Machine Learning Applied to Predicting Microorganism Growth Temperatures and Enzyme Catalytic Optima-Reference-Cited by-同舟云学术

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Machine Learning Applied to Predicting Microorganism Growth Temperatures and Enzyme Catalytic Optima

Published:2019-05-22 Issue:6 Volume:8 Page:1411-1420
ISSN:2161-5063
Container-title:ACS Synthetic Biology
language:en
Short-container-title:ACS Synth. Biol.

Author:

Li Gang¹,Rabe Kersten S.²^ORCID,Nielsen Jens¹³,Engqvist Martin K. M.¹^ORCID

Affiliation:

1. Department of Biology and Biological Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden

2. Institute for Biological Interfaces 1 (IBG 1), Karlsruhe Institute of Technology (KIT), Group for Molecular Evolution, 76131 Karlsruhe, Germany

3. Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark

Funder

Novo Nordisk

Helmholtz-Gemeinschaft

Knut och Alice Wallenbergs Stiftelse

H2020 Marie Sklodowska-Curie Actions

Publisher

American Chemical Society (ACS)

Subject

Biochemistry, Genetics and Molecular Biology (miscellaneous),Biomedical Engineering,General Medicine

Link

https://pubs.acs.org/doi/pdf/10.1021/acssynbio.9b00099

Reference63 articles.

1. Enzymes from extremophiles

2. Potential and utilization of thermophiles and thermostable enzymes in biorefining

3. Hyperthermophilic Enzymes: Sources, Uses, and Molecular Mechanisms for Thermostability

4. Developments in industrially important thermostable enzymes: a review

5. Extremozymes—biocatalysts with unique properties from extremophilic microorganisms

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