scRGCL: a cell type annotation method for single-cell RNA-seq data using residual graph convolutional neural network with contrastive learning
Lin Yuan(Hubei University of Medicine), De-Shuang Huang(Eastern Institute of Technology), Yufeng Jiang(Qilu University of Technology), Shengguo Sun(Qilu University of Technology), Chun-Hou Zheng(Anhui University), Lan Ye(Second Hospital of Shandong University), Qinhu Zhang(Eastern Institute of Technology)
Cited by 46
Related Papers
Emerging roles of circRNA_001569 targeting miR-145 in the proliferation and invasion of colorectal cancer
|Oncotarget|2016|431
Exosome–transmitted long non-coding RNA PTENP1 suppresses bladder cancer progression
|Molecular Cancer|2018|298
A cohort study of diabetic patients and diabetic foot ulceration patients in China
|Wound Repair and Regeneration|2015|181
Epidemiology of Type 2 Diabetic Foot Problems and Predictive Factors for Amputation in China
|The International Journal of Lower Extremity Wounds|2015|153
Circulating miR-497 and miR-663b in plasma are potential novel biomarkers for bladder cancer
|Scientific Reports|2015|119