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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis
Xiangjie Li, Kui Wang, Yafei Lyu, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 304

Showing 1-25 of 304 citing articles:

AI in health and medicine
Pranav Rajpurkar, Emma Chen, Oishi Banerjee, et al.
Nature Medicine (2022) Vol. 28, Iss. 1, pp. 31-38
Closed Access | Times Cited: 1274
Benchmarking atlas-level data integration in single-cell genomics
Malte D. Luecken, Maren Büttner, Kridsadakorn Chaichoompu, et al.
Nature Methods (2021) Vol. 19, Iss. 1, pp. 41-50
Open Access | Times Cited: 719
SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network
Jian Hu, Xiangjie Li, Kyle Coleman, et al.
Nature Methods (2021) Vol. 18, Iss. 11, pp. 1342-1351
Open Access | Times Cited: 556
APOE and TREM2 regulate amyloid-responsive microglia in Alzheimer’s disease
Aivi T. Nguyen, Kui Wang, Gang Hu, et al.
Acta Neuropathologica (2020) Vol. 140, Iss. 4, pp. 477-493
Open Access | Times Cited: 159
Multi-omics integration in the age of million single-cell data
Zhen Miao, Benjamin D. Humphreys, Andrew P. McMahon, et al.
Nature Reviews Nephrology (2021) Vol. 17, Iss. 11, pp. 710-724
Open Access | Times Cited: 140
Modeling gene regulatory networks using neural network architectures
Hantao Shu, Jingtian Zhou, Qiuyu Lian, et al.
Nature Computational Science (2021) Vol. 1, Iss. 7, pp. 491-501
Closed Access | Times Cited: 107
Machine learning meets omics: applications and perspectives
Rufeng Li, Lixin Li, Yungang Xu, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Closed Access | Times Cited: 104
Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions
Nan Yang, Javier Del Ser, Simon Walsh, et al.
Information Fusion (2022) Vol. 82, pp. 99-122
Open Access | Times Cited: 98
A review of deep learning applications in human genomics using next-generation sequencing data
W. Alharbi, Mamoon Rashid
Human Genomics (2022) Vol. 16, Iss. 1
Open Access | Times Cited: 64
Graph embedding and Gaussian mixture variational autoencoder network for end-to-end analysis of single-cell RNA sequencing data
Junlin Xu, Jielin Xu, Yajie Meng, et al.
Cell Reports Methods (2023) Vol. 3, Iss. 1, pp. 100382-100382
Open Access | Times Cited: 62
Deep learning applications in single-cell genomics and transcriptomics data analysis
Nafiseh Erfanian, A. Ali Heydari, Adib Miraki Feriz, et al.
Biomedicine & Pharmacotherapy (2023) Vol. 165, pp. 115077-115077
Open Access | Times Cited: 47
Review of single-cell RNA-seq data clustering for cell-type identification and characterization
Shi-Xiong Zhang, Xiangtao Li, Jiecong Lin, et al.
RNA (2023) Vol. 29, Iss. 5, pp. 517-530
Open Access | Times Cited: 44
Batch alignment of single-cell transcriptomics data using deep metric learning
Xiaokang Yu, Xinyi Xu, Jingxiao Zhang, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 37
Integration of Single-Cell RNA-Seq Datasets: A Review of Computational Methods
Daehee Hwang, Geun Hee Han, Eun‐Soo Jung, et al.
Molecules and Cells (2023) Vol. 46, Iss. 2, pp. 106-119
Open Access | Times Cited: 36
The implications of single-cell RNA-seq analysis in prostate cancer: unraveling tumor heterogeneity, therapeutic implications and pathways towards personalized therapy
Dechao Feng, Weizhen Zhu, Jie Wang, et al.
Military Medical Research (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 20
Effective multi-modal clustering method via skip aggregation network for parallel scRNA-seq and scATAC-seq data
Dayu Hu, Ke Liang, Zhibin Dong, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 2
Open Access | Times Cited: 18
Iterative transfer learning with neural network for clustering and cell type classification in single-cell RNA-seq analysis
Jian Hu, Xiangjie Li, Gang Hu, et al.
Nature Machine Intelligence (2020) Vol. 2, Iss. 10, pp. 607-618
Open Access | Times Cited: 113
Deep soft K-means clustering with self-training for single-cell RNA sequence data
Liang Chen, Weinan Wang, Yuyao Zhai, et al.
NAR Genomics and Bioinformatics (2020) Vol. 2, Iss. 2
Open Access | Times Cited: 92
Statistical and machine learning methods for spatially resolved transcriptomics with histology
Jian Hu, Amelia Schroeder, Kyle Coleman, et al.
Computational and Structural Biotechnology Journal (2021) Vol. 19, pp. 3829-3841
Open Access | Times Cited: 69
Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer’s disease: review, recommendation, implementation and application
Minghui Wang, Won‐Min Song, Ming Chen, et al.
Molecular Neurodegeneration (2022) Vol. 17, Iss. 1
Open Access | Times Cited: 63
Single-cell sequencing: a promising approach for uncovering the mechanisms of tumor metastasis
Yingying Han, Dan Wang, Lushan Peng, et al.
Journal of Hematology & Oncology (2022) Vol. 15, Iss. 1
Open Access | Times Cited: 61
Fly Cell Atlas: a single-cell transcriptomic atlas of the adult fruit fly
Hongjie Li, Jasper Janssens, Maxime De Waegeneer, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 60
Advancing Drug Discovery for Neurological Disorders Using iPSC-Derived Neural Organoids
Gianluca Costamagna, Giacomo P. Comi, Stefania Corti
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 5, pp. 2659-2659
Open Access | Times Cited: 53
A joint deep learning model enables simultaneous batch effect correction, denoising, and clustering in single-cell transcriptomics
Justin Lakkis, David Wang, Yuanchao Zhang, et al.
Genome Research (2021) Vol. 31, Iss. 10, pp. 1753-1766
Open Access | Times Cited: 53
Self-supervised contrastive learning for integrative single cell RNA-seq data analysis
Wenkai Han, Yuqi Cheng, Jiayang Chen, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 5
Open Access | Times Cited: 52
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