A. R. Lowe

cellPLATO: an unsupervised method for identifying cell behaviour in heterogeneous cell trajectory data

cellPLATO identifies cell behaviour in trajectory data by clustering morphology and motility metrics, revealing IL-15's role in increasing NK cell migration plasticity.

Virtual perturbations to assess explainability of deep-learning based cell fate predictors

The paper introduces virtual perturbation to assess explainability of a deep-learning cell fate predictor, showing it captures known biological relationships.

Learning dynamic image representations for self-supervised cell cycle annotation

This paper introduces a self-supervised framework using image autoencoders and dynamic time series analysis to annotate cell cycle phases in single-cell trajectories.

Epithelioids: Self-sustaining 3D epithelial cultures to study long-term processes

This paper introduces epithelioids, a 3D culture system for mouse and human epithelia that maintains structure and function over long periods, enabling study of long-term biological processes.

Learning the rules of cell competition without prior scientific knowledge

This paper develops a deep learning model to learn the rules of cell competition from time-lapse microscopy data and identifies cell density as the key factor in determining cell fate.

Automated deep lineage tree analysis using a Bayesian single cell tracking approach

This paper introduces an automated deep lineage tree analysis method using Bayesian single-cell tracking to study cell cycle heritability in live-cell imaging data.

Dual role of Miro protein clusters in mitochondrial cristae organisation and ER-Mitochondria Contact Sites

This study identifies Miro protein clusters' role in mitochondrial cristae organisation and ER-mitochondria contact sites using super-resolution microscopy and knockout models.