A practical application of generative adversarial networks for RNA-seq analysis to predict the molecular progress of Alzheimer’s disease

September 22, 2020 Leave a comment 1,992 Views

Next-generation sequencing (NGS) technology has become a powerful tool for dissecting the molecular and pathological signatures of a variety of human...

A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis

February 27, 2020 Leave a comment 3,081 Views

Single-cell RNA sequencing (scRNA-seq) is an emerging technology that can assess the function of an individual cell and cell-to-cell variability at the single cell level in an unbiased manner. Dimensionality reduction is an essential first step in downstream analysis of ...

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Tag Archives: Generative adversarial networks

A practical application of generative adversarial networks for RNA-seq analysis to predict the molecular progress of Alzheimer’s disease

A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis

SiT – spatial isoform transcriptomics

Analysis of single-cell rna-seq data

AllenDigger – spatial expression data visualization, spatial heterogeneity delineation, and single-cell registration based on the Allen Brain Atlas

New research identifies an inaccuracy in the single cell GENCODE gene model

Femtosecond laser microdissection for isolation of regenerating C. elegans neurons for single-cell RNA sequencing

Spatial epigenome–transcriptome co-profiling of mammalian tissues

A protocol for single nucleus RNA-seq from frozen skeletal muscle