Birs- 19w5032: Frontiers in Single-cell Technology, Applications and Data Analysis
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Title: Understanding gene regulation using single cell RNA-seq data (Abstract ID: A6)
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Title: Single Cell Transcriptomics: Denoising and Transfer Learning (Abstract ID: A13)
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Title: Effectively comparing publicly available single cell datasets: a case study in glioblastoma multiforme (Abstract ID: A15)
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Title: Fast and accurate alignment of single-cell RNA-seq samples using kernel density matching (Abstract ID: A8)
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Title: Reconstructing gene regulatory dynamics along pseudotemporal trajectories using single-cell RNA-seq (Abstract ID: A11)
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Title: Impact of Misspecified Dependence on Clustering of RNA-seq Gene Expression Profiles (Abstract ID: A1)
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Title: Penalized Latent Dirichlet Allocation Model in Single Cell RNA Sequencing (Abstract ID: A4)
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Title: iDEA: Integrative Differential Expression Analysis and Gene Set Enrichment Analysis in Single Cell RNAseq Studies (Abstract ID: A7)
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Title: A statistical simulator scDesign for rational scRNA-seq experimental design (Abstract ID: A9)
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Title: Single cell transcriptomics and fate mapping of ependymal cells reveals an absence of neural stem cell function (Abstract ID: A10)
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