Identification of cell-type-specific genes in multimodal single-cell data using deep neural network algorithm

The emergence of single-cell RNA sequencing (scRNA-seq) technology makes it possible to measure DNA, RNA, and protein in a single cell. Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq) is a powerful multimodal single-cell research innovation, allowing researchers to capture...

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Bibliographic Details
Published in:	Computers in biology and medicine Vol. 166; p. 107498
Main Authors:	Qian, Weiye, Yang, Zhiyuan
Format:	Journal Article
Language:	English
Published:	United States Elsevier Ltd 01.11.2023 Elsevier Limited
Subjects:	Algorithms Artificial neural networks Bioinformatics Bone marrow Bone Marrow Cells - cytology Bone Marrow Cells - metabolism Cell differentiation Datasets Deep Learning Differentiation (biology) Epitopes Gene expression Gene Expression Profiling - methods Gene sequencing Genes Heterogeneity Humans Internal Medicine Machine learning Multimodal single-cell study Neural networks Neural Networks, Computer Neural stem cells Neutrophils Optimization techniques Other Proteins Ribonucleic acid RNA RNA-protein interactions Sequence Analysis, RNA - methods Single-Cell Analysis - methods Stem cells Student's t-test Transcriptome - genetics Transcriptomes Deep learning Bioinformatics Multimodal single-cell study
ISSN:	0010-4825, 1879-0534, 1879-0534
Online Access:	Get full text
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