AIMC Topic: Islets of Langerhans

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Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis.

Nature communications May 11, 2020
Single-cell RNA sequencing (scRNA-seq) can characterize cell types and states through unsupervised clustering, but the ever increasing number of cells and batch effect impose computational challenges. We present DESC, an unsupervised deep embedding a...
Humans Algorithms Animals Leukocytes, Mononuclear Deep Learning Single-Cell Analysis RNA-Seq Mice Monocytes Cluster Analysis Bone Marrow Retina Gene Expression Regulation Macaca Islets of Langerhans
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Deep learning models predict regulatory variants in pancreatic islets and refine type 2 diabetes association signals.

eLife Jan 27, 2020
Genome-wide association analyses have uncovered multiple genomic regions associated with T2D, but identification of the causal variants at these remains a challenge. There is growing interest in the potential of deep learning models - which predict e...
Humans Deep Learning Genome-Wide Association Study Diabetes Mellitus, Type 2 Genetic Predisposition to Disease Polymorphism, Single Nucleotide Epigenomics Signal Transduction Models, Theoretical Chromatin Islets of Langerhans
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Single-cell ATAC-Seq in human pancreatic islets and deep learning upscaling of rare cells reveals cell-specific type 2 diabetes regulatory signatures.

Molecular metabolism Dec 20, 2019
OBJECTIVE: Type 2 diabetes (T2D) is a complex disease characterized by pancreatic islet dysfunction, insulin resistance, and disruption of blood glucose levels. Genome-wide association studies (GWAS) have identified > 400 independent signals that enc...
Humans Gene Expression Profiling Deep Learning Diabetes Mellitus, Type 2 Single-Cell Analysis Polymorphism, Single Nucleotide Chromatin Immunoprecipitation Sequencing Islets of Langerhans
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