Birs- 19w5032: Frontiers in Single-cell Technology, Applications and Data Analysis

  1. Title:
    Understanding gene regulation using single cell RNA-seq data (Abstract ID: A6)

    Speaker:

    Link:

  2. Title:
    Single Cell Transcriptomics: Denoising and Transfer Learning (Abstract ID: A13)

    Speaker:

    Link:

  3. Title:
    Effectively comparing publicly available single cell datasets: a case study in glioblastoma multiforme (Abstract ID: A15)

    Speaker:

    Link:

  4. Title:
    Fast and accurate alignment of single-cell RNA-seq samples using kernel density matching (Abstract ID: A8)

    Speaker:

    Link:

  5. Title:
    Reconstructing gene regulatory dynamics along pseudotemporal trajectories using single-cell RNA-seq (Abstract ID: A11)

    Speaker:

    Link:

  6. Title:
    Impact of Misspecified Dependence on Clustering of RNA-seq Gene Expression Profiles (Abstract ID: A1)

    Speaker:

    Link:

  7. Title:
    Penalized Latent Dirichlet Allocation Model in Single Cell RNA Sequencing (Abstract ID: A4)

    Speaker:

    Link:

  8. Title:
    iDEA: Integrative Differential Expression Analysis and Gene Set Enrichment Analysis in Single Cell RNAseq Studies (Abstract ID: A7)

    Speaker:

    Link:

  9. Title:
    A statistical simulator scDesign for rational scRNA-seq experimental design (Abstract ID: A9)

    Speaker:

    Link:

  10. Title:
    Single cell transcriptomics and fate mapping of ependymal cells reveals an absence of neural stem cell function (Abstract ID: A10)

    Speaker:

    Link: