Reinforcement Learning for Bioretrosynthesis-Reference-Cited by-同舟云学术

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Reinforcement Learning for Bioretrosynthesis

Published:2019-12-16 Issue:1 Volume:9 Page:157-168
ISSN:2161-5063
Container-title:ACS Synthetic Biology
language:en
Short-container-title:ACS Synth. Biol.

Author:

Koch Mathilde¹,Duigou Thomas¹,Faulon Jean-Loup¹²³^ORCID

Affiliation:

1. Micalis Institute, INRA, AgroParisTech, Université Paris-Saclay, 78350 Jouy-en-Josas, France

2. iSSB Laboratory, Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 91057 Evry, France

3. SYNBIOCHEM Center, School of Chemistry, University of Manchester, Manchester M13 9PL, U.K.

Funder

Engineering and Physical Sciences Research Council

Agence Nationale de la Recherche

Biotechnology and Biological Sciences Research Council

Minist?re des Arm?es

?cole Polytechnique

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.9b00447

Reference64 articles.

1. DESHARKY: automatic design of metabolic pathways for optimal cell growth

2. PathPred: an enzyme-catalyzed metabolic pathway prediction server

3. Discovery and analysis of novel metabolic pathways for the biosynthesis of industrial chemicals: 3-hydroxypropanoate

4. Enumerating metabolic pathways for the production of heterologous target chemicals in chassis organisms

5. Metabolic engineering of Escherichia coli for direct production of 1,4-butanediol

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