Frontiers in Single-cell Technology, Applications and Data Analysis
Videos from BIRS Workshop
Yunlong Liu, Indiana University School of Medicine
Monday Feb 25, 2019 14:18 - 15:01
Understanding gene regulation using single cell RNA-seq data (Abstract ID: A6)
Nancy Zhang, University of Pennsylvania
Monday Feb 25, 2019 15:32 - 16:17
Single Cell Transcriptomics: Denoising and Transfer Learning (Abstract ID: A13)
Paul Gordon, University of Calgary
Monday Feb 25, 2019 16:21 - 16:55
Effectively comparing publicly available single cell datasets: a case study in glioblastoma multiforme (Abstract ID: A15)
Mengjie Chen, University of Chicago
Tuesday Feb 26, 2019 09:32 - 10:32
Fast and accurate alignment of single-cell RNA-seq samples using kernel density matching (Abstract ID: A8)
Hongkai Ji, Johns Hopkins Bloomberg School of Public Health
Tuesday Feb 26, 2019 13:32 - 14:26
Reconstructing gene regulatory dynamics along pseudotemporal trajectories using single-cell RNA-seq (Abstract ID: A11)
Alexander de Leon, University of Calgary
Tuesday Feb 26, 2019 14:29 - 15:10
Impact of Misspecified Dependence on Clustering of RNA-seq Gene Expression Profiles (Abstract ID: A1)
Jean Wu, Brown University
Wednesday Feb 27, 2019 08:57 - 09:29
Penalized Latent Dirichlet Allocation Model in Single Cell RNA Sequencing (Abstract ID: A4)
Xiang Zhou, University of Michigan
Wednesday Feb 27, 2019 09:45 - 10:31
iDEA: Integrative Differential Expression Analysis and Gene Set Enrichment Analysis in Single Cell RNAseq Studies (Abstract ID: A7)
Jingyi Jessica Li, University of California Los Angeles
Wednesday Feb 27, 2019 11:00 - 12:01
A statistical simulator scDesign for rational scRNA-seq experimental design (Abstract ID: A9)
Jo Stratton, Hotchkiss Brain Institute
Thursday Feb 28, 2019 09:02 - 09:31
Single cell transcriptomics and fate mapping of ependymal cells reveals an absence of neural stem cell function (Abstract ID: A10)
