Supervised and unsupervised deep learning-based approaches for studying DNA replication spatiotemporal dynamics

This project aimed to demonstrate how deep learning could be leveraged for studying DNA replication spatiotemporal dynamics. Through well-characterised cellular models, we showed in both supervised and unsupervised settings how convolutional neural networks could successfully identify aberrant DNA r...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Ng-Kee-Kwong, Julian, Chen, Naiming, Buonomo, Sara
Format:	Dataset
Sprache:	eng
Schlagworte:	Biological Sciences::Molecular Biology Biophysics and Biochemistry Convolutional neural network Cyclin E Deep learning DNA replication Machine learning Replication timing RIF1 Self-supervised learning Spatiotemporal organisation
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