Probabilistic modelling approach for pseudotime estimation in single cells and populations
Speaker: Cristopher Yau, Reader in Computational Biology, Centre for Computational Biology, University of Birmingham, UK.
This biostatistics seminar is jointly organised with the Sven Furberg Seminars in Bioinformatics and Statistical Genomics. At the end of the seminar simple food and refreshments will be served.
Single cell pseudotime algorithms attempt to extract temporal information from cross-sectional molecular profiles of single cells. Whilst there are a plethora of algorithmic methods for single cell pseudotime estimation, our focus has been on the development of model-based probabilistic approaches using Bayesian inference. I shall talk about a suite of pseudotime methods that have been developed in my group and their application to single cell genomics and beyond.
Dr. Yau obtained his PhD in Statistics at The Queen's College, University of Oxford, in 2009. He was a Medical Research Council Research postdoctoral fellow in Biomedical Informatics up to 2012. He was then appointed as a Lecturer in Statistics at the Imperial College London. He launched the Genomic Medicine Group at the Welcome Trust Centre for Human Genetics in 2014 and became Associate Professor in 2016. Since 2017 he is a Reader in Computational Biology in Statistical Machine Learning for BioHealth at the University of Birmingham.