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Technologies for whole-cell modeling: Genome-wide reconstruction of a cell in silico.
Kaizu, Kazunari; Takahashi, Koichi.
Afiliación
  • Kaizu K; RIKEN Center for Biosystems Dynamics Research, Osaka, Japan.
  • Takahashi K; RIKEN Center for Biosystems Dynamics Research, Osaka, Japan.
Dev Growth Differ ; 65(9): 554-564, 2023 Dec.
Article en En | MEDLINE | ID: mdl-37856476
ABSTRACT
With advances in high-throughput, large-scale in vivo measurement and genome modification techniques at the single-nucleotide level, there is an increasing demand for the development of new technologies for the flexible design and control of cellular systems. Computer-aided design is a powerful tool to design new cells. Whole-cell modeling aims to integrate various cellular subsystems, determine their interactions and cooperative mechanisms, and predict comprehensive cellular behaviors by computational simulations on a genome-wide scale. It has been applied to prokaryotes, yeasts, and higher eukaryotic cells, and utilized in a wide range of applications, including production of valuable substances, drug discovery, and controlled differentiation. Whole-cell modeling, consisting of several thousand elements with diverse scales and properties, requires innovative model construction, simulation, and analysis techniques. Furthermore, whole-cell modeling has been extended to multiple scales, including high-resolution modeling at the single-nucleotide and single-amino acid levels and multicellular modeling of tissues and organs. This review presents an overview of the current state of whole-cell modeling, discusses the novel computational and experimental technologies driving it, and introduces further developments toward multihierarchical modeling on a whole-genome scale.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Biología de Sistemas / Modelos Biológicos Idioma: En Revista: Dev Growth Differ Año: 2023 Tipo del documento: Article País de afiliación: Japón

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Biología de Sistemas / Modelos Biológicos Idioma: En Revista: Dev Growth Differ Año: 2023 Tipo del documento: Article País de afiliación: Japón