Cargando…
The influence of spatial and temporal resolutions on the analysis of cell-cell interaction: a systematic study for time-lapse microscopy applications
Cell-cell interactions are an observable manifestation of underlying complex biological processes occurring in response to diversified biochemical stimuli. Recent experiments with microfluidic devices and live cell imaging show that it is possible to characterize cell kinematics via computerized alg...
Autores principales: | Comes, M. C., Casti, P., Mencattini, A., Di Giuseppe, D., Mermet-Meillon, F., De Ninno, A., Parrini, M. C., Businaro, L., Di Natale, C., Martinelli, E. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6494897/ https://www.ncbi.nlm.nih.gov/pubmed/31043687 http://dx.doi.org/10.1038/s41598-019-42475-5 |
Ejemplares similares
-
Machine learning phenomics (MLP) combining deep learning with time-lapse-microscopy for monitoring colorectal adenocarcinoma cells gene expression and drug-response
por: D’Orazio, M., et al.
Publicado: (2022) -
Discovering the hidden messages within cell trajectories using a deep learning approach for in vitro evaluation of cancer drug treatments
por: Mencattini, A., et al.
Publicado: (2020) -
NeuriTES. Monitoring neurite changes through transfer entropy and semantic segmentation in bright-field time-lapse microscopy
por: Mencattini, Arianna, et al.
Publicado: (2021) -
Accelerating the experimental responses on cell behaviors: a long-term prediction of cell trajectories using Social Generative Adversarial Network
por: Comes, Maria Colomba, et al.
Publicado: (2020) -
Deep-Manager: a versatile tool for optimal feature selection in live-cell imaging analysis
por: Mencattini, A., et al.
Publicado: (2023)