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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:

Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model
F. William Townes, Stephanie C. Hicks, Martin J. Aryee, et al.
Genome biology (2019) Vol. 20, Iss. 1
Open Access | Times Cited: 412

Showing 1-25 of 412 citing articles:

Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression
Christoph Hafemeister, Rahul Satija
Genome biology (2019) Vol. 20, Iss. 1
Open Access | Times Cited: 3337
Eleven grand challenges in single-cell data science
David Lähnemann, Johannes Köster, Ewa Szczurek, et al.
Genome biology (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 992
The art of using t-SNE for single-cell transcriptomics
Dmitry Kobak, Philipp Berens
Nature Communications (2019) Vol. 10, Iss. 1
Open Access | Times Cited: 816
Orchestrating single-cell analysis with Bioconductor
Robert A. Amezquita, Aaron T. L. Lun, Étienne Becht, et al.
Nature Methods (2019) Vol. 17, Iss. 2, pp. 137-145
Open Access | Times Cited: 697
Robust decomposition of cell type mixtures in spatial transcriptomics
Dylan Cable, Evan Murray, Luli S. Zou, et al.
Nature Biotechnology (2021) Vol. 40, Iss. 4, pp. 517-526
Open Access | Times Cited: 656
Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients
Pierre Bost, Amir Giladi, Yang Liu, et al.
Cell (2020) Vol. 181, Iss. 7, pp. 1475-1488.e12
Open Access | Times Cited: 473
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: 436
Statistics or biology: the zero-inflation controversy about scRNA-seq data
Ruochen Jiang, Tianyi Sun, Dongyuan Song, et al.
Genome biology (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 425
Identifying gene expression programs of cell-type identity and cellular activity with single-cell RNA-Seq
Dylan Kotliar, Adrian Veres, M. Aurel Nagy, et al.
eLife (2019) Vol. 8
Open Access | Times Cited: 374
Probabilistic harmonization and annotation of single‐cell transcriptomics data with deep generative models
Chenling Xu, Romain Lopez, Edouard Mehlman, et al.
Molecular Systems Biology (2021) Vol. 17, Iss. 1
Open Access | Times Cited: 362
Comparison and evaluation of statistical error models for scRNA-seq
Saket Choudhary, Rahul Satija
Genome biology (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 315
Benchmarking of cell type deconvolution pipelines for transcriptomics data
Francisco Avila Cobos, José Alquicira-Hernández, Joseph E. Powell, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 309
muscat detects subpopulation-specific state transitions from multi-sample multi-condition single-cell transcriptomics data
Helena L. Crowell, Charlotte Soneson, Pierre‐Luc Germain, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 307
Droplet scRNA-seq is not zero-inflated
Valentine Svensson
Nature Biotechnology (2020) Vol. 38, Iss. 2, pp. 147-150
Open Access | Times Cited: 300
Spatially resolved multi-omics deciphers bidirectional tumor-host interdependence in glioblastoma
Vidhya M. Ravi, Paulina Will, Jan Kueckelhaus, et al.
Cancer Cell (2022) Vol. 40, Iss. 6, pp. 639-655.e13
Open Access | Times Cited: 297
A systematic evaluation of single-cell RNA-sequencing imputation methods
Wenpin Hou, Zhicheng Ji, Hongkai Ji, et al.
Genome biology (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 233
glmGamPoi: fitting Gamma-Poisson generalized linear models on single cell count data
Constantin Ahlmann-Eltze, Wolfgang Huber
Bioinformatics (2020) Vol. 36, Iss. 24, pp. 5701-5702
Open Access | Times Cited: 196
Accuracy, robustness and scalability of dimensionality reduction methods for single-cell RNA-seq analysis
Shiquan Sun, Jiaqiang Zhu, Ying Ma, et al.
Genome biology (2019) Vol. 20, Iss. 1
Open Access | Times Cited: 170
Separating measurement and expression models clarifies confusion in single-cell RNA sequencing analysis
Abhishek Sarkar, Matthew Stephens
Nature Genetics (2021) Vol. 53, Iss. 6, pp. 770-777
Open Access | Times Cited: 161
Interpretable factor models of single-cell RNA-seq via variational autoencoders
Valentine Svensson, Adam Gayoso, Nir Yosef, et al.
Bioinformatics (2020) Vol. 36, Iss. 11, pp. 3418-3421
Open Access | Times Cited: 157
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: 145
Single-cell eQTL models reveal dynamic T cell state dependence of disease loci
Aparna Nathan, Samira Asgari, Kazuyoshi Ishigaki, et al.
Nature (2022) Vol. 606, Iss. 7912, pp. 120-128
Open Access | Times Cited: 128
Normalizing and denoising protein expression data from droplet-based single cell profiling
Matthew P. Mulè, Andrew J. Martins, John S. Tsang
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 117
RNA velocity unraveled
Gennady Gorin, Meichen Fang, Tara Chari, et al.
PLoS Computational Biology (2022) Vol. 18, Iss. 9, pp. e1010492-e1010492
Open Access | Times Cited: 112
Analytic Pearson residuals for normalization of single-cell RNA-seq UMI data
Jan Lause, Philipp Berens, Dmitry Kobak
Genome biology (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 104
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