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Respectful Modeling: Addressing Uncertainty in Dynamic System Models for Molecular Biology.
Tsigkinopoulou, Areti; Baker, Syed Murtuza; Breitling, Rainer.
Afiliação
  • Tsigkinopoulou A; Manchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, Faculty of Science and Engineering, University of Manchester, 131 Princess Street, Manchester M1 7DN, UK.
  • Baker SM; Manchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, Faculty of Science and Engineering, University of Manchester, 131 Princess Street, Manchester M1 7DN, UK.
  • Breitling R; Manchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, Faculty of Science and Engineering, University of Manchester, 131 Princess Street, Manchester M1 7DN, UK. Electronic address: rainer.breitling@manchester.ac.uk.
Trends Biotechnol ; 35(6): 518-529, 2017 06.
Article em En | MEDLINE | ID: mdl-28094080
Although there is still some skepticism in the biological community regarding the value and significance of quantitative computational modeling, important steps are continually being taken to enhance its accessibility and predictive power. We view these developments as essential components of an emerging 'respectful modeling' framework which has two key aims: (i) respecting the models themselves and facilitating the reproduction and update of modeling results by other scientists, and (ii) respecting the predictions of the models and rigorously quantifying the confidence associated with the modeling results. This respectful attitude will guide the design of higher-quality models and facilitate the use of models in modern applications such as engineering and manipulating microbial metabolism by synthetic biology.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biologia Computacional / Biologia Sintética / Modelos Biológicos Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biologia Computacional / Biologia Sintética / Modelos Biológicos Idioma: En Ano de publicação: 2017 Tipo de documento: Article