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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:

Benchmarking spatial and single-cell transcriptomics integration methods for transcript distribution prediction and cell type deconvolution
Bin Li, Wen Zhang, Chuang Guo, et al.
Nature Methods (2022) Vol. 19, Iss. 6, pp. 662-670
Closed Access | Times Cited: 272

Showing 1-25 of 272 citing articles:

Best practices for single-cell analysis across modalities
Lukas Heumos, Anna C. Schaar, Christopher Lance, et al.
Nature Reviews Genetics (2023) Vol. 24, Iss. 8, pp. 550-572
Open Access | Times Cited: 496
An introduction to spatial transcriptomics for biomedical research
Cameron G. Williams, Hyun Jae Lee, Takahiro Asatsuma, et al.
Genome Medicine (2022) Vol. 14, Iss. 1
Open Access | Times Cited: 458
High resolution mapping of the tumor microenvironment using integrated single-cell, spatial and in situ analysis
Amanda Janesick, Robert Shelansky, Andrew D. Gottscho, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 247
Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST
Yahui Long, Kok Siong Ang, Mengwei Li, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 224
Spatially resolved multiomics of human cardiac niches
Kazumasa Kanemaru, James Cranley, Daniele Muraro, et al.
Nature (2023) Vol. 619, Iss. 7971, pp. 801-810
Open Access | Times Cited: 151
The scverse project provides a computational ecosystem for single-cell omics data analysis
Isaac Virshup, Danila Bredikhin, Lukas Heumos, et al.
Nature Biotechnology (2023) Vol. 41, Iss. 5, pp. 604-606
Closed Access | Times Cited: 145
High resolution mapping of the breast cancer tumor microenvironment using integrated single cell, spatial and in situ analysis of FFPE tissue
Amanda Janesick, Robert Shelansky, Andrew D. Gottscho, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 121
A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics
Haoyang Li, Juexiao Zhou, Zhongxiao Li, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 120
An integrated single cell and spatial transcriptomic map of human white adipose tissue
Lucas Massier, Jutta Jalkanen, Merve Elmastas, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 83
Spatially resolved transcriptomics: a comprehensive review of their technological advances, applications, and challenges
Mengnan Cheng, Yujia Jiang, Jiangshan Xu, et al.
Journal of genetics and genomics/Journal of Genetics and Genomics (2023) Vol. 50, Iss. 9, pp. 625-640
Open Access | Times Cited: 73
scDesign3 generates realistic in silico data for multimodal single-cell and spatial omics
Dongyuan Song, Qingyang Wang, Guanao Yan, et al.
Nature Biotechnology (2023) Vol. 42, Iss. 2, pp. 247-252
Closed Access | Times Cited: 72
SODB facilitates comprehensive exploration of spatial omics data
Zhiyuan Yuan, Wentao Pan, Xuan Zhao, et al.
Nature Methods (2023) Vol. 20, Iss. 3, pp. 387-399
Closed Access | Times Cited: 70
Spatially resolved transcriptomics reveals genes associated with the vulnerability of middle temporal gyrus in Alzheimer’s disease
Shuo Chen, Yuzhou Chang, Liangping Li, et al.
Acta Neuropathologica Communications (2022) Vol. 10, Iss. 1
Open Access | Times Cited: 69
Reconstruction of the tumor spatial microenvironment along the malignant-boundary-nonmalignant axis
Zhenzhen Xun, Xinyu Ding, Yao Zhang, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 69
A Review of Single-Cell RNA-Seq Annotation, Integration, and Cell–Cell Communication
Changde Cheng, Wenan Chen, Hongjian Jin, et al.
Cells (2023) Vol. 12, Iss. 15, pp. 1970-1970
Open Access | Times Cited: 57
Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope
Xiaomeng Wan, Jiashun Xiao, Sindy Sing Ting Tam, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 54
Benchmarking spatial clustering methods with spatially resolved transcriptomics data
Zhiyuan Yuan, Fangyuan Zhao, Senlin Lin, et al.
Nature Methods (2024) Vol. 21, Iss. 4, pp. 712-722
Closed Access | Times Cited: 50
Optimizing Xenium In Situ data utility by quality assessment and best practice analysis workflows
Sergio Marco Salas, Paulo Czarnewski, Louis B. Kuemmerle, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 44
SRTsim: spatial pattern preserving simulations for spatially resolved transcriptomics
Jiaqiang Zhu, Lulu Shang, Xiang Zhou
Genome biology (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 44
Spatial transcriptomics reveals discrete tumour microenvironments and autocrine loops within ovarian cancer subclones
Elena Denisenko, Leanne de Kock, Adeline Tan, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 34
Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics
Gunsagar S. Gulati, Jeremy Philip D’Silva, Yunhe Liu, et al.
Nature Reviews Molecular Cell Biology (2024) Vol. 26, Iss. 1, pp. 11-31
Closed Access | Times Cited: 31
Deciphering the spatial landscape and plasticity of immunosuppressive fibroblasts in breast cancer
Hugo Croizer, Rana Mhaidly, Yann Kieffer, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 30
Multiscale biochemical mapping of the brain through deep-learning-enhanced high-throughput mass spectrometry
Yuxuan Richard Xie, Daniel C. Castro, Stanislav S. Rubakhin, et al.
Nature Methods (2024) Vol. 21, Iss. 3, pp. 521-530
Open Access | Times Cited: 27
BIDCell: Biologically-informed self-supervised learning for segmentation of subcellular spatial transcriptomics data
Xiaohang Fu, Yingxin Lin, David Lin, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 26
The covariance environment defines cellular niches for spatial inference
Doron Haviv, Ján Remšík, Mohamed I. Gatie, et al.
Nature Biotechnology (2024)
Open Access | Times Cited: 23
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