Graph attention network with convolutional layer for predicting gene regulations from single-cell ribonucleic acid sequence data-Reference-Cited by-同舟云学术

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Graph attention network with convolutional layer for predicting gene regulations from single-cell ribonucleic acid sequence data

Published:2024-10 Issue: Volume:136 Page:108938
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Liu Junjiang,Zhou Shusen^ORCID,Ma Jing,Zang Mujun,Liu Chanjuan,Liu Tong,Wang Qingjun

Publisher

Elsevier BV

Reference28 articles.

1. Gene regulatory network inference in single-cell biology;Akers;Curr. Opin. Syst. Biol.,2021

2. Gene regulation inference from single-cell RNA-seq data with linear differential equations and velocity inference;Aubin-Frankowski;Bioinformatics,2020

3. DeepDRIM: A deep neural network to reconstruct cell-type-specific gene regulatory network using single-cell RNA-seq data;Chen;Brief. Bioinform.,2021

4. Graph attention network for link prediction of gene regulations from single-cell RNA-sequencing data;Chen;Bioinformatics,2022

5. Network inference with Granger causality ensembles on single-cell transcriptomics;Deshpande;Cell Rep.,2022

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