Article

Integrating Pathway Knowledge with Deep Neural Networks to Reduce the Dimensionality in Single-Cell RNA-Seq Data

2021-09-08

Abstract excerpt

<title>Abstract</title> <p>BackgroundSingle-cell RNA sequencing (scRNA-seq) data provides valuable insights into cellular heterogeneity which is significantly improving the current knowledge on biology and human disease. One of the main applications of scRNA-seq data analysis is the identification of new cell types and cell states. Deep neural networks (DNNs) are among the best methods to address this problem. Ho...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 80087710-e21f-5fd1-b8f1-f0e0fec57660
DOI: 10.21203/rs.3.rs-847372/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Integrating Pathway Knowledge with Deep Neural Networks to Reduce the Dimensionality in Single-Cell RNA-Seq DataDOI 10.21203/rs.3.rs-847372/v1Read

scGNN: a novel graph neural network framework for single-cell RNA-Seq analysesSemantic proximity Read

Unsupervised cell functional annotation for single-cell RNA-SeqSemantic proximity Read

A multimodal deep learning model to infer cell-type-specific functional gene networksSemantic proximity Read

MCNET: Multi-Omics Integration for Gene Regulatory Network Inference from scRNA-seqSemantic proximity Read

Inferring Disease Progressive Stages in Single-Cell Transcriptomics Using Weakly-Supervised Deep Learning ApproachSemantic proximity Read

DrivAER: Identification of driving transcriptional programs in single-cell RNA sequencing dataSemantic proximity Read

Deep learning for inferring gene relationships from single-cell expression dataSemantic proximity Read

Knowledge-primed neural networks enable biologically interpretable deep learning on single-cell sequencing dataSemantic proximity Read

DeepDRIM: a deep neural network to reconstruct cell-type-specific gene regulatory network using single-cell RNA-Seq DataSemantic proximity Read

HD Spot: Interpretable Deep Learning Classification of Single Cell Transcript DataSemantic proximity Read

CellGO: A novel deep learning-based framework and webserver for cell type-specific gene function interpretationSemantic proximity Read

Spatial Transcriptomic Cell-type Deconvolution Using Graph Neural NetworksSemantic proximity Read