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Building the next generation of virtual cells to understand cellular biology.
Johnson, Graham T; Agmon, Eran; Akamatsu, Matthew; Lundberg, Emma; Lyons, Blair; Ouyang, Wei; Quintero-Carmona, Omar A; Riel-Mehan, Megan; Rafelski, Susanne; Horwitz, Rick.
Afiliación
  • Johnson GT; Allen Institute for Cell Science, Seattle, Washington.
  • Agmon E; Center for Cell Analysis and Modeling, University of Connecticut Health, Farmington, Connecticut.
  • Akamatsu M; Department of Biology, University of Washington, Seattle, Washington.
  • Lundberg E; Department of Applied Physics, Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden; Department of Bioengineering, Stanford University, Stanford, California; Department of Pathology, Stanford University, Stanford, California; Chan Zuckerberg Biohub, San Francisco, Califo
  • Lyons B; Allen Institute for Cell Science, Seattle, Washington.
  • Ouyang W; Department of Applied Physics, Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden.
  • Quintero-Carmona OA; Department of Biology, University of Richmond, Richmond, Virginia.
  • Riel-Mehan M; Allen Institute for Cell Science, Seattle, Washington.
  • Rafelski S; Allen Institute for Cell Science, Seattle, Washington.
  • Horwitz R; Allen Institute for Cell Science, Seattle, Washington. Electronic address: rickh@alleninstitute.org.
Biophys J ; 122(18): 3560-3569, 2023 09 19.
Article en En | MEDLINE | ID: mdl-37050874
Cell science has made significant progress by focusing on understanding individual cellular processes through reductionist approaches. However, the sheer volume of knowledge collected presents challenges in integrating this information across different scales of space and time to comprehend cellular behaviors, as well as making the data and methods more accessible for the community to tackle complex biological questions. This perspective proposes the creation of next-generation virtual cells, which are dynamic 3D models that integrate information from diverse sources, including simulations, biophysical models, image-based models, and evidence-based knowledge graphs. These virtual cells would provide statistically accurate and holistic views of real cells, bridging the gap between theoretical concepts and experimental data, and facilitating productive new collaborations among researchers across related fields.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Biophys J Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Biophys J Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos