دورية أكاديمية
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teemi: An open-source literate programming approach for iterative design-build-test-learn cycles in bioengineering.

التفاصيل البيبلوغرافية
العنوان: teemi: An open-source literate programming approach for iterative design-build-test-learn cycles in bioengineering.
المؤلفون: Petersen SD; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark., Levassor L; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark.; Department of Biotechnology and Biomedicine, Technical University of Denmark, Kgs. Lyngby, Denmark., Pedersen CM; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark., Madsen J; Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark., Hansen LG; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark., Zhang J; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark., Haidar AK; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark., Frandsen RJN; Department of Biotechnology and Biomedicine, Technical University of Denmark, Kgs. Lyngby, Denmark., Keasling JD; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark.; Joint BioEnergy Institute, Emeryville, California, United States of America.; Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.; Department of Chemical and Biomolecular Engineering, Department of Bioengineering, University of California, Berkeley, California, United States of America.; Center for Synthetic Biochemistry, Institute for Synthetic Biology, Shenzhen Institutes of Advanced Technologies, Shenzhen, China., Weber T; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark., Sonnenschein N; Department of Biotechnology and Biomedicine, Technical University of Denmark, Kgs. Lyngby, Denmark., K Jensen M; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark.
المصدر: PLoS computational biology [PLoS Comput Biol] 2024 Mar 08; Vol. 20 (3), pp. e1011929. Date of Electronic Publication: 2024 Mar 08 (Print Publication: 2024).
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE
أسماء مطبوعة: Original Publication: San Francisco, CA : Public Library of Science, [2005]-
مواضيع طبية MeSH: Metabolic Engineering* , Bioengineering*, Synthetic Biology ; Biomedical Engineering ; Saccharomyces cerevisiae
مستخلص: Synthetic biology dictates the data-driven engineering of biocatalysis, cellular functions, and organism behavior. Integral to synthetic biology is the aspiration to efficiently find, access, interoperate, and reuse high-quality data on genotype-phenotype relationships of native and engineered biosystems under FAIR principles, and from this facilitate forward-engineering strategies. However, biology is complex at the regulatory level, and noisy at the operational level, thus necessitating systematic and diligent data handling at all levels of the design, build, and test phases in order to maximize learning in the iterative design-build-test-learn engineering cycle. To enable user-friendly simulation, organization, and guidance for the engineering of biosystems, we have developed an open-source python-based computer-aided design and analysis platform operating under a literate programming user-interface hosted on Github. The platform is called teemi and is fully compliant with FAIR principles. In this study we apply teemi for i) designing and simulating bioengineering, ii) integrating and analyzing multivariate datasets, and iii) machine-learning for predictive engineering of metabolic pathway designs for production of a key precursor to medicinal alkaloids in yeast. The teemi platform is publicly available at PyPi and GitHub.
Competing Interests: The authors have read the journal’s policy and the authors of this manuscript have the following competing interests: M.K.J., L.G.H. J.D.K. and J.Z. are inventors on pending patent applications. M.K.J., L.G.H., J.D.K., and J.Z. have financial interest in Biomia Aps. J.D.K. also has a financial interest in Amyris, Lygos, Demetrix, Napigen, Apertor Pharmaceuticals, Maple Bio, Ansa Biotechnologies, Berkeley Yeast, and Zero Acre Farms. The remaining authors declare no competing interests.
(Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)
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تواريخ الأحداث: Date Created: 20240308 Date Completed: 20240322 Latest Revision: 20240322
رمز التحديث: 20240322
مُعرف محوري في PubMed: PMC10954146
DOI: 10.1371/journal.pcbi.1011929
PMID: 38457467
قاعدة البيانات: MEDLINE
الوصف
تدمد:1553-7358
DOI:10.1371/journal.pcbi.1011929