Research Themes and Publications
Machine learning for the identification of senescent cells in cancer and aging
SAMP-Score: A morphology-based machine learning method for identifying novel pro-senescence compounds in p16 positive cancers
bioRxiv
The promise of machine learning approaches to capture cellular senescence heterogeneity
Nature Aging
SenPred: A single-cell RNA sequencing-based machine learning pipeline to classify senescent cells for the detection of an in vivo senescent cell burden
Genome Medicine
Yearning for Machine Learning: Opportunities for the classification and characterisation of senescence
Cell and Tissue Research
Senescence-associated morphological profiles (SAMPs): An image-based phenotypic profiling method for evaluating the inter and intra model heterogeneity of senescence
Aging
Methodology development for assessment of exosomes in cancer and aging
Isolation methodology is essential to the evaluation of the extracellular vesicle component of the senescence‐associated secretory phenotype
Journal of Extracellular Vesicles
The Bright and Dark Side of Extracellular Vesicles in the Senescence-Associated Secretory Phenotype
Mechanisms of Ageing and Development
Exploring the paradox of senescence markers in cancer cells
The paradox of senescent-marker positive (SenMark+) cancer cells: challenges and opportunities
NPJ Aging
CRISPR / siRNA screening in senescence
Death-seq and ye shall find: A novel screening strategy for dying cells
Cell Metabolism
Early growth response 2 (EGR2) is a novel regulator of the senescence programme
Aging Cell