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GMOCU: Digital Documentation, Management, and Biological Risk Assessment of Genetic Parts.
Wagner, Christoph; Urquiza-Garcia, Uriel; Zurbriggen, Matias D; Beyer, Hannes M.
Afiliação
  • Wagner C; Institute of Synthetic Biology, Heinrich-Heine-University Düsseldorf, Universitätsstrasse 1, D-40225, Düsseldorf, Germany.
  • Urquiza-Garcia U; Institute of Synthetic Biology, Heinrich-Heine-University Düsseldorf, Universitätsstrasse 1, D-40225, Düsseldorf, Germany.
  • Zurbriggen MD; CEPLAS-Cluster of Excellence on Plant Sciences, Heinrich-Heine-University Düsseldorf, Universitätsstrasse 1, D-40225, Düsseldorf, Germany.
  • Beyer HM; Institute of Synthetic Biology, Heinrich-Heine-University Düsseldorf, Universitätsstrasse 1, D-40225, Düsseldorf, Germany.
Adv Biol (Weinh) ; 8(4): e2300529, 2024 04.
Article em En | MEDLINE | ID: mdl-38263723
ABSTRACT
The continuous evolution of molecular biology and gene synthesis methods paired with an ever-increasing potential of synthetic biology approaches and genome engineering toolkits enables the rapid design of genetic bioparts and genetically modified organisms. Although various software solutions assist with specific design tasks and challenges, lab internal documentation and ensuring compliance with governmental regulations on biosafety assessment of the generated organisms remain the responsibility of individual academic researchers. This results in inconsistent and redundant documentation regimes and a significant time and labor burden. GMOCU (GMO documentation) is a standardized semi-automatic user-oriented software approach -written in Python and freely available- that unifies lab internal data documentation on genetic parts and genetically modified organisms (GMOs). It automatizes biological risk evaluations and maintains a shared up-to-date inventory of bioparts for team-wide data navigation and sharing. GMOCU further enables data export into customizable formats suitable for scientific publications, official biosafety documents, and the research community.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Documentação Tipo de estudo: Etiology_studies / Risk_factors_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Documentação Tipo de estudo: Etiology_studies / Risk_factors_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article