Speaker
Nikolay Oskolkov
(Lund University, Department of Biology)
Description
Next Generation Sequencing technologies gave rise to manifolds of Biomedical Big Data which is particularly manifested in the area of single cell transcriptomics where millions of cells are sequenced. Deep Learning (DL) is an ideal framework for analyzing large amounts of data and building predictive models for Clinical Diagnostics within the concept of Precision Medicine. Bayesian DL adds an important level of patient safety providing uncertainties to the biomedical predictions. Here, using single-cell transcriptomics data I demonstrate how Bayesian DL improves the accuracy of discovering novel cell sub-populations and dramatically outperforms classical methods when handling unknown cell sub-types.
