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CarveAdornCurate: a versatile cloud-based platform for constructing multiscale metabolic models.

Yang Cheng1, Wenwen Yu1, Xinyu Bi1

  • 1Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China; Science Center for Future Foods, Jiangnan University, Wuxi 214122, China.

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PubMed
Summary
This summary is machine-generated.

We developed CarveAdornCurate (CAC), a new workflow for de novo multiscale modeling. CAC simplifies the creation of complex cellular models, making them more accessible for research and metabolic engineering applications.

Keywords:
CarveAdornCuratecloud-based web toolgenome-scale metabolic modelsmachine learningmultiscale modeling

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Area of Science:

  • Systems Biology
  • Metabolic Engineering
  • Computational Biology

Background:

  • Multiscale modeling offers insights into cellular functions but is hindered by the complex creation of genome-scale metabolic models (GEMs).
  • Current methods for building multiscale models are time-consuming and require extensive manual curation, limiting their widespread adoption.

Purpose of the Study:

  • To introduce a novel, automated workflow, CarveAdornCurate (CAC), for the de novo construction of multiscale models.
  • To enhance the accessibility and efficiency of creating sophisticated cellular models for biological research.

Main Methods:

  • The Carve module generates an ensemble of genetically supported GEMs.
  • The Adorn module upgrades these GEMs into multiscale models.
  • The Curate module identifies key features within the generated models.
  • Integration into a cloud-based platform for user accessibility.

Main Results:

  • Successful construction of CAC-based multiscale models for Corynebacterium glutamicum and Yarrowia lipolytica.
  • Demonstrated potential of CAC models in guiding metabolic engineering strategies.
  • Validation of CAC as an efficient and user-friendly tool for multiscale model generation.

Conclusions:

  • CAC provides an efficient and accessible solution for de novo multiscale model construction.
  • The workflow streamlines the process, overcoming limitations of existing methods.
  • CAC facilitates advancements in systems biology and metabolic engineering by enabling easier model development.