Learning dynamical models of single and collective cell migration: a review

D Brückner, CP Broedersz - Reports on Progress in Physics, 2024 - iopscience.iop.org
Single and collective cell migration are fundamental processes critical for physiological
phenomena ranging from embryonic development and immune response to wound healing …

Data science in cell imaging

MK Driscoll, A Zaritsky - Journal of cell science, 2021 - journals.biologists.com
Cell imaging has entered the 'Big Data'era. New technologies in light microscopy and
molecular biology have led to an explosion in high-content, dynamic and multidimensional …

Learning biophysical determinants of cell fate with deep neural networks

CJ Soelistyo, G Vallardi, G Charras… - Nature machine …, 2022 - nature.com
Deep learning is now a powerful tool in microscopy data analysis, and is routinely used for
image processing applications such as segmentation and denoising. However, it has rarely …

Whole-genome screens reveal regulators of differentiation state and context-dependent migration in human neutrophils

NM Belliveau, MJ Footer, E Akdoǧan… - Nature …, 2023 - nature.com
Neutrophils are the most abundant leukocyte in humans and provide a critical early line of
defense as part of our innate immune system. We perform a comprehensive, genome-wide …

Accurate cell tracking and lineage construction in live-cell imaging experiments with deep learning

E Moen, E Borba, G Miller, M Schwartz, D Bannon… - Biorxiv, 2019 - biorxiv.org
Live-cell imaging experiments have opened an exciting window into the behavior of living
systems. While these experiments can produce rich data, the computational analysis of …

Orientation-invariant autoencoders learn robust representations for shape profiling of cells and organelles

J Burgess, JJ Nirschl, MC Zanellati, A Lozano… - Nature …, 2024 - nature.com
Cell and organelle shape are driven by diverse genetic and environmental factors and thus
accurate quantification of cellular morphology is essential to experimental cell biology …

Physics-informed deep learning characterizes morphodynamics of Asian soybean rust disease

H Cavanagh, A Mosbach, G Scalliet, R Lind… - Nature …, 2021 - nature.com
Medicines and agricultural biocides are often discovered using large phenotypic screens
across hundreds of compounds, where visible effects of whole organisms are compared to …

DynaMorph: self-supervised learning of morphodynamic states of live cells

Z Wu, BB Chhun, G Popova, SM Guo… - Molecular biology of …, 2022 - Am Soc Cell Biol
A cell's shape and motion represent fundamental aspects of cell identity and can be highly
predictive of function and pathology. However, automated analysis of the morphodynamic …

Cell migration CRISPRi screens in human neutrophils reveal regulators of context-dependent migration and differentiation state

NM Belliveau, MJ Footer, E Akdogan, AP van Loon… - bioRxiv, 2022 - biorxiv.org
Neutrophils are the most abundant leukocyte in humans and provide a critical early line of
defense as part of our innate immune system. Their exquisite sensitivity to chemical …

[HTML][HTML] Generative modeling of biological shapes and images using a probabilistic [... formula...]-shape sampler

ET Winn-Nuñez, H Witt, D Bhaskar, RY Huang… - bioRxiv, 2024 - ncbi.nlm.nih.gov
Understanding morphological variation is an important task in many areas of computational
biology. Recent studies have focused on developing computational tools for the task of sub …