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Cell Movement

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Deep Learning-Based Cell Tracking in Deforming Organs and Moving Animals.

Methods in molecular biology (Clifton, N.J.)
Cell tracking is an essential step in extracting cellular signals from moving cells, which is vital for understanding the mechanisms underlying various biological functions and processes, particularly in organs such as the brain and heart. However, c...

Development and validation of AI/ML derived splice-switching oligonucleotides.

Molecular systems biology
Splice-switching oligonucleotides (SSOs) are antisense compounds that act directly on pre-mRNA to modulate alternative splicing (AS). This study demonstrates the value that artificial intelligence/machine learning (AI/ML) provides for the identificat...

Using deep learning for predicting the dynamic evolution of breast cancer migration.

Computers in biology and medicine
BACKGROUND: Breast cancer (BC) remains a prevalent health concern, with metastasis as the main driver of mortality. A detailed understanding of metastatic processes, particularly cell migration, is fundamental to improve therapeutic strategies. The w...

A self-supervised embedding of cell migration features for behavior discovery over cell populations.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Recent studies point out that the dynamics and interaction of cell populations within their environment are related to several biological processes in immunology. Hence, single-cell analysis in immunology now relies on spati...

Deciphering lung adenocarcinoma prognosis and immunotherapy response through an AI-driven stemness-related gene signature.

Journal of cellular and molecular medicine
Lung adenocarcinoma (LUAD) is a leading cause of cancer-related deaths, and improving prognostic accuracy is vital for personalised treatment approaches, especially in the context of immunotherapy. In this study, we constructed an artificial intellig...

Collection of microrobots for gentle cell manipulation.

Science robotics
Optically actuated soft microrobotic tools were designed for cell transportation, manipulation, and cell-to-cell interactions.

Aberrant migration features in primary skin fibroblasts of Huntington's disease patients hold potential for unraveling disease progression using an image based machine learning tool.

Computers in biology and medicine
Huntington's disease (HD) is a complex neurodegenerative disorder with considerable heterogeneity in clinical manifestations. While CAG repeat length is a known predictor of disease severity, this heterogeneity suggests the involvement of additional ...

Forecasting and Predicting Stochastic Agent-Based Model Data with Biologically-Informed Neural Networks.

Bulletin of mathematical biology
Collective migration is an important component of many biological processes, including wound healing, tumorigenesis, and embryo development. Spatial agent-based models (ABMs) are often used to model collective migration, but it is challenging to thor...

Interpretable Fine-Grained Phenotypes of Subcellular Dynamics via Unsupervised Deep Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Uncovering fine-grained phenotypes of live cell dynamics is pivotal for a comprehensive understanding of the heterogeneity in healthy and diseased biological processes. However, this endeavor poses significant technical challenges for unsupervised ma...

Deep learning reveals a damage signalling hierarchy that coordinates different cell behaviours driving wound re-epithelialisation.

Development (Cambridge, England)
One of the key tissue movements driving closure of a wound is re-epithelialisation. Earlier wound healing studies describe the dynamic cell behaviours that contribute to wound re-epithelialisation, including cell division, cell shape changes and cell...