Single-cell classification using graph convolutional networks

Single-cell classification using graph convolutional networks

Abstract Background Analyzing single-cell RNA sequencing (scRNAseq) data plays an important role in understanding the intrinsic and extrinsic cellular processes in biological and biomedical research. One significant effort in this area is the identification of cell types. With the availability of a...

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Bibliographic Details
Main Authors: Tianyu Wang, Jun Bai, Sheida Nabavi
Format: Article
Language:English
Published: BMC 2021-07-01
Series:BMC Bioinformatics
Subjects:
Single cell RNA sequencing
Cell classification
Deep learning
Graph convolutional neural network
Convolutional neural network
Online Access:https://doi.org/10.1186/s12859-021-04278-2

Internet

https://doi.org/10.1186/s12859-021-04278-2

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