Starts 23 Feb 2021 15:00
Ends 23 Feb 2021 17:00
Central European Time
Zoom Meeting
Zoom Meeting ID to attend the online seminar: 475-819-702

Join Zoom Meeting:https://zoom.us/j/475819702

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Abstract: Recent advances in single-cell technologies provide a unique opportunity to study tumor heterogeneity, which is one of the main problems in developing therapies for cancer patients. Associated technological and biological problems such as sparsity of the data and stochasticity of gene expression provide fundamental challenges for rigorous subpopulation identification. Random Matrix Theory (RMT) allows to deal with those challenges in a systematic way thanks to the universality properties at the eigenvalue and eigenvector levels . Synergetic use with machine learning algorithms provides a unique avenue to distinguish single-cell heterogeneous subpopulations. I will present an introduction to the applications of RMT in single-cell biology and an application to construct a cell atlas of the human and mouse prostate epithelium