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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:

Inferring spatial and signaling relationships between cells from single cell transcriptomic data
Zixuan Cang, Qing Nie
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 290

Showing 1-25 of 290 citing articles:

Inference and analysis of cell-cell communication using CellChat
Suoqin Jin, Christian F. Guerrero‐Juarez, Lihua Zhang, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 4457
Exploring tissue architecture using spatial transcriptomics
Anjali Rao, Dalia Barkley, Gustavo S. França, et al.
Nature (2021) Vol. 596, Iss. 7871, pp. 211-220
Open Access | Times Cited: 1045
Deciphering cell–cell interactions and communication from gene expression
Erick Armingol, Adam Officer, Olivier Harismendy, et al.
Nature Reviews Genetics (2020) Vol. 22, Iss. 2, pp. 71-88
Open Access | Times Cited: 899
Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics
Sophia K. Longo, Margaret Guo, Andrew L. Ji, et al.
Nature Reviews Genetics (2021) Vol. 22, Iss. 10, pp. 627-644
Open Access | Times Cited: 670
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
stLearn: integrating spatial location, tissue morphology and gene expression to find cell types, cell-cell interactions and spatial trajectories within undissociated tissues
Duy Pham, Xiao Tan, Jun Xu, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 308
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
The landscape of aging
Yusheng Cai, Wei Song, Jiaming Li, et al.
Science China Life Sciences (2022) Vol. 65, Iss. 12, pp. 2354-2454
Open Access | Times Cited: 239
Spatial components of molecular tissue biology
Giovanni Palla, David S. Fischer, Aviv Regev, et al.
Nature Biotechnology (2022) Vol. 40, Iss. 3, pp. 308-318
Closed Access | Times Cited: 234
Predicting cell-to-cell communication networks using NATMI
Rui Hou, Elena Denisenko, Huan Ting Ong, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 202
Screening cell–cell communication in spatial transcriptomics via collective optimal transport
Zixuan Cang, Yanxiang Zhao, Axel A. Almet, et al.
Nature Methods (2023) Vol. 20, Iss. 2, pp. 218-228
Open Access | Times Cited: 192
Advances in spatial transcriptomic data analysis
Ruben Dries, Jiaji Chen, Natalie Del Rossi, et al.
Genome Research (2021) Vol. 31, Iss. 10, pp. 1706-1718
Open Access | Times Cited: 172
Alignment and integration of spatial transcriptomics data
Ron Zeira, Max Land, Alexander Strzalkowski, et al.
Nature Methods (2022) Vol. 19, Iss. 5, pp. 567-575
Open Access | Times Cited: 154
Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues
Duy Pham, Xiao Tan, Brad Balderson, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 152
The landscape of cell–cell communication through single-cell transcriptomics
Axel A. Almet, Zixuan Cang, Suoqin Jin, et al.
Current Opinion in Systems Biology (2021) Vol. 26, pp. 12-23
Open Access | Times Cited: 146
Statistical and machine learning methods for spatially resolved transcriptomics data analysis
Zexian Zeng, Yawei Li, Yiming Li, et al.
Genome biology (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 125
Characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomic data with nonuniform cellular densities
Brendan Miller, Dhananjay Bambah-Mukku, Catherine Dulac, et al.
Genome Research (2021) Vol. 31, Iss. 10, pp. 1843-1855
Open Access | Times Cited: 124
Modeling intercellular communication in tissues using spatial graphs of cells
David S. Fischer, Anna C. Schaar, Fabian J. Theis
Nature Biotechnology (2022) Vol. 41, Iss. 3, pp. 332-336
Open Access | Times Cited: 124
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
Explainable multiview framework for dissecting spatial relationships from highly multiplexed data
Jovan Tanevski, Ricardo O. Ramirez Flores, Attila Gábor, et al.
Genome biology (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 110
Polony gels enable amplifiable DNA stamping and spatial transcriptomics of chronic pain
Xiaonan Fu, Li Sun, Runze Dong, et al.
Cell (2022) Vol. 185, Iss. 24, pp. 4621-4633.e17
Open Access | Times Cited: 96
Spatial omics: Navigating to the golden era of cancer research
Yingcheng Wu, Yifei Cheng, Xiangdong Wang, et al.
Clinical and Translational Medicine (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 91
Knowledge-graph-based cell-cell communication inference for spatially resolved transcriptomic data with SpaTalk
Xin Shao, Chengyu Li, Haihong Yang, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 91
CellChat for systematic analysis of cell-cell communication from single-cell and spatially resolved transcriptomics
Suoqin Jin, Maksim V. Plikus, Qing Nie
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 91
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