| Literature DB >> 35472832 |
Jia Lu1, Emrah Şimşek1, Anita Silver1, Lingchong You2.
Abstract
Spatial patterning of cell populations is a ubiquitous phenomenon in nature. Patterns occur at various length and time scales and exhibit immense diversity. In addition to offering a deeper understanding of the emergence of patterns in nature, the ability to program synthetic patterns using living cells has the potential for broad applications. To date, however, progress in engineering pattern formation has been hampered by technical challenges. In this Review, we discuss recent advances in programming pattern formation in terms of biological insights, experimental and computational tool development, and potential applications.Entities:
Keywords: Machine learning; Pattern formation; Reaction-diffusion models; Synthetic biology; Turing patterns
Mesh:
Year: 2022 PMID: 35472832 PMCID: PMC9158282 DOI: 10.1016/j.cbpa.2022.102147
Source DB: PubMed Journal: Curr Opin Chem Biol ISSN: 1367-5931 Impact factor: 8.972