Cargando…
Recognition and reconstruction of cell differentiation patterns with deep learning
Cell lineage decisions occur in three-dimensional spatial patterns that are difficult to identify by eye. There is an ongoing effort to replicate such patterns using mathematical modeling. One approach uses long ranging cell-cell communication to replicate common spatial arrangements like checkerboa...
Autores principales: | Dirk, Robin, Fischer, Jonas L., Schardt, Simon, Ankenbrand, Markus J., Fischer, Sabine C. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10631711/ https://www.ncbi.nlm.nih.gov/pubmed/37889897 http://dx.doi.org/10.1371/journal.pcbi.1011582 |
Ejemplares similares
-
Adjusting the range of cell–cell communication enables fine-tuning of cell fate patterns from checkerboard to engulfing
por: Schardt, Simon, et al.
Publicado: (2023) -
The salt-and-pepper pattern in mouse blastocysts is compatible with signaling beyond the nearest neighbors
por: Fischer, Sabine C., et al.
Publicado: (2023) -
Exploring the Application of Pattern Recognition and Machine Learning for Identifying Movement Phenotypes During Deep Squat and Hurdle Step Movements
por: Remedios, Sarah M., et al.
Publicado: (2020) -
Artificial Intelligence and Deep Learning for Advancing PET Image Reconstruction: State-of-the-Art and Future Directions
por: Hellwig, Dirk, et al.
Publicado: (2023) -
A deep-learning automated image recognition method for measuring pore patterns in closely related bolivinids and calibration for quantitative nitrate paleo-reconstructions
por: Govindankutty Menon, Anjaly, et al.
Publicado: (2023)