Single-Cell Plus - Data Science Challenges in Single-Cell Research
Videos from BIRS Workshop
Jake Yeung, Institute of Science and Technology Austria
Monday Jul 3, 2023 09:29 - 09:46
Greater than the sum of the parts: Learning relationships between histone modifications in single cells
Keegan Korthauer, University of British Columbia
Monday Jul 3, 2023 09:46 - 10:05
Probabilistic modelling of single-cell methylation sequencing data reveals regions that are informative of cell type and cell state
Zhana Duren, Clemson University
Monday Jul 3, 2023 10:06 - 10:27
Modelling gene regulation via integrative analysis of single cell multi-omics data
Sunyoung Shin, POSTECH
Monday Jul 3, 2023 10:48 - 11:09
Scalable test of statistical significance for protein-DNA binding changes with insertion and deletion of bases in the genome
Hongkai Ji, Johns Hopkins Bloomberg School of Public Health
Monday Jul 3, 2023 11:11 - 11:35
Discussion Session
Yuanhua Huang, University of Hong Kong
Monday Jul 3, 2023 16:13 - 16:28
Modelling of cellular dynamics on differentiation and lineage
Kwangmoon Park, University of Wisconsin-Madison
Monday Jul 3, 2023 16:35 - 16:50
Joint tensor modeling of single cell 3D genome and epigenetic data with Muscle
Zhanying Feng, Chinese Academy of Sciences, Academy of Mathematics and Systems Science
Monday Jul 3, 2023 16:58 - 17:23
Combinatorial regulons (cregulon): a novel optimization model for unraveling cellular identity and state transitions through single multi-omics data
Sara Mostafavi, University of Washington
Tuesday Jul 4, 2023 09:13 - 09:38
Day 2: Advances in single-cell RNA-Seq data
Agus Salim, University of Melbourne
Tuesday Jul 4, 2023 11:14 - 11:31
RUV-III-NB: A robust method for normalization of single cell RNA-seq data
Mattew Ritchie, The Walter and Eliza Hall Institute of Medical Research
Tuesday Jul 4, 2023 11:31 - 11:46
Modelling group heteroscedasticity in single-cell RNA-seq pseudo-bulk data
Jessica Mar, University of Queensland
Tuesday Jul 4, 2023 11:47 - 12:03
One of these cells is not like the other - modelling variability of gene expression in single cell data
Zheng Ye, Fred Hutchinson Cancer Center
Tuesday Jul 4, 2023 16:11 - 16:29
Robust normalization and integration of single-cell protein expression across CITE-seq datasets
Kelly Street, University of Southern California
Tuesday Jul 4, 2023 16:30 - 16:46
Improving the Resolution of Single-Cell TCR-seq
David Shih, Hong Kong University
Tuesday Jul 4, 2023 16:46 - 17:09
Integrative analysis of scRNA-seq, scTCR-seq, and TCR-seq to identify and characterize antigen-specific T cells
Yu Li, Chinese University of Hong Kong
Wednesday Jul 5, 2023 09:30 - 09:42
scNovel: a neural network framework for novel rare cell detection of single-cell transcriptome data
Yue Li, McGill University
Wednesday Jul 5, 2023 09:43 - 10:03
Guided-topic modelling of single-cell transcriptomes enables sub-cell-type and disease-subtype deconvolution of bulk transcriptomes
Shila Ghazanfar, University of Sydney
Wednesday Jul 5, 2023 10:05 - 10:24
Mosaic single cell data integration
Emma Zhang, Emory University
Wednesday Jul 5, 2023 11:03 - 11:19
Cell-type-specific co-expression inference from single cell RNA-sequencing data
Jingyi Jessica Li, University of California Los Angeles
Wednesday Jul 5, 2023 11:21 - 11:41
ClusterDE: a post-clustering differentially expressed (DE) gene identification method robust to false-positive inflation caused by double-dipping
Rafael Irizarry, Dana-Farber Cancer Institute
Thursday Jul 6, 2023 09:19 - 09:44
Statistical challenges in Single-Cell RNA-Seq and spatial transcriptomics
Xiting Yan, Yale University School of Medicine
Thursday Jul 6, 2023 09:45 - 10:03
Spatial Deconvolution Method Considering Platform Effect Removal, Sparsity and Spatial Information
Can Yang, The Hong Kong University of Science and Technology
Thursday Jul 6, 2023 10:03 - 10:26
SpatialScope: A unified approach for integrating spatial and single-cell transcriptomics data using deep generative models
Jean Yee Hwa Yang, The University of Sydney
Thursday Jul 6, 2023 11:01 - 11:18
Biologically-informed self-supervised learning for segmentation of subcellular spatial transcriptomics data
Mellisa Davis, University of Adelaide
Thursday Jul 6, 2023 11:20 - 11:38
Rethinking assumptions in spatial molecular data analysis: the role and impact of library size normalisation
Haiyan Huang, University of California, Berkeley
Thursday Jul 6, 2023 11:38 - 11:59
Discussion
Di Wu, University of North Carolina at Chapel Hill
Thursday Jul 6, 2023 16:09 - 16:24
Gene set tests and cell-cell communication in scRNA-seq data
Ellis Patrick, The University of Sydney
Thursday Jul 6, 2023 16:42 - 16:57
Identifying changes in cell states related to their spatial context in tissue microenvironment
Joshua Ho, University of Hong Kong
Friday Jul 7, 2023 09:06 - 09:20
Scalable analysis methods for single cell omics data and lineage tracing
Zuoheng Wang, Yale University
Friday Jul 7, 2023 09:20 - 09:38
Graphical generative model for identification of disease associated perturbations to intercellular communications in single-cell RNA sequencing data
Angela Wu, Hong Kong University of Science and Technology
Friday Jul 7, 2023 09:38 - 09:54
Cross-species single-cell atlases: analysis and challenges
Hongyu Zhao, Yale University
Friday Jul 7, 2023 09:57 - 10:14
An informatics framework for assembling human cell atlases as a digital life
Ge Gao, Peking University
Friday Jul 7, 2023 10:14 - 10:39
Delineate the regulatory map in silico
