Mechanism of ciliary train switch and cargo recognition
A study by the Pigino Group at Human Technopole reveals that the conversion from anterograde to retrograde intraflagellar transport requires the complete disassembly of anterograde trains at the ciliary tip and provides the mechanisms for direction-specific cargo binding and transport in cilia.
Chan Zuckerberg Initiative grant to the Glastonbury Group
The Glastonbury Group is among the recipients of the Data Insights Cycle 3 awards. The aim of the grant is to develop a machine learning model that identifies disease-relevant cell subpopulations whilst predicting a phenotype/disease of interest from large-scale single-cell RNA-seq data.
Machine learning reveals hidden features in histology images
Researchers at Human Technopole developed a self-supervised machine learning model that combines histology, gene expression, and genetic variation to automatically identify and cluster distinct tissue substructures, cells, and pathological features in human tissues.
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