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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:

Efficient integration of heterogeneous single-cell transcriptomes using Scanorama
Brian Hie, Bryan D. Bryson, Bonnie Berger
Nature Biotechnology (2019) Vol. 37, Iss. 6, pp. 685-691
Open Access | Times Cited: 759

Showing 1-25 of 759 citing articles:

Comprehensive Integration of Single-Cell Data
Tim Stuart, Andrew Butler, Paul Hoffman, et al.
Cell (2019) Vol. 177, Iss. 7, pp. 1888-1902.e21
Open Access | Times Cited: 12804
Fast, sensitive and accurate integration of single-cell data with Harmony
Ilya Korsunsky, Nghia Millard, Jean Fan, et al.
Nature Methods (2019) Vol. 16, Iss. 12, pp. 1289-1296
Open Access | Times Cited: 5944
Dictionary learning for integrative, multimodal and scalable single-cell analysis
Yuhan Hao, Tim Stuart, Madeline H. Kowalski, et al.
Nature Biotechnology (2023) Vol. 42, Iss. 2, pp. 293-304
Open Access | Times Cited: 1322
A pan-cancer single-cell transcriptional atlas of tumor infiltrating myeloid cells
Sijin Cheng, Ziyi Li, Ranran Gao, et al.
Cell (2021) Vol. 184, Iss. 3, pp. 792-809.e23
Open Access | Times Cited: 969
Single-cell transcriptional diversity is a hallmark of developmental potential
Gunsagar S. Gulati, Shaheen S. Sikandar, Daniel J. Wesche, et al.
Science (2020) Vol. 367, Iss. 6476, pp. 405-411
Open Access | Times Cited: 933
A benchmark of batch-effect correction methods for single-cell RNA sequencing data
Hoa Thi Tran, Kok Siong Ang, Marion Chevrier, et al.
Genome biology (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 855
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: 792
BBKNN: fast batch alignment of single cell transcriptomes
Krzysztof Polański, Matthew D. Young, Zhichao Miao, et al.
Bioinformatics (2019) Vol. 36, Iss. 3, pp. 964-965
Open Access | Times Cited: 740
The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans
The Tabula Sapiens Consortium, Robert C. Jones, Jim Karkanias, et al.
Science (2022) Vol. 376, Iss. 6594
Open Access | Times Cited: 660
Single‐cell RNA sequencing technologies and applications: A brief overview
Dragomirka Jovic, Xue Liang, Zeng Hua, et al.
Clinical and Translational Medicine (2022) Vol. 12, Iss. 3
Open Access | Times Cited: 655
scMC learns biological variation through the alignment of multiple single-cell genomics datasets
Lihua Zhang, Qing Nie
Genome biology (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 654
Single-cell transcriptomics of human T cells reveals tissue and activation signatures in health and disease
Peter A. Szabo, Hanna Mendes Levitin, Michelle Miron, et al.
Nature Communications (2019) Vol. 10, Iss. 1
Open Access | Times Cited: 611
Comparative cellular analysis of motor cortex in human, marmoset and mouse
Trygve E. Bakken, Nikolas L. Jorstad, Qiwen Hu, et al.
Nature (2021) Vol. 598, Iss. 7879, pp. 111-119
Open Access | Times Cited: 571
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: 506
A multimodal cell census and atlas of the mammalian primary motor cortex
Edward M. Callaway, Hong‐Wei Dong, Joseph R. Ecker, et al.
Nature (2021) Vol. 598, Iss. 7879, pp. 86-102
Open Access | Times Cited: 460
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: 387
Mapping single-cell data to reference atlases by transfer learning
Mohammad Lotfollahi, Mohsen Naghipourfar, Malte D. Luecken, et al.
Nature Biotechnology (2021) Vol. 40, Iss. 1, pp. 121-130
Open Access | Times Cited: 386
Profiling Cell Type Abundance and Expression in Bulk Tissues with CIBERSORTx
Chloé B. Steen, Chih Long Liu, Ash A. Alizadeh, et al.
Methods in molecular biology (2020), pp. 135-157
Open Access | Times Cited: 372
Joint probabilistic modeling of single-cell multi-omic data with totalVI
Adam Gayoso, Zoë Steier, Romain Lopez, et al.
Nature Methods (2021) Vol. 18, Iss. 3, pp. 272-282
Open Access | Times Cited: 368
Interpretation of T cell states from single-cell transcriptomics data using reference atlases
Massimo Andreatta, Jesús Corría-Osorio, Sören Müller, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 363
Computational principles and challenges in single-cell data integration
Ricard Argelaguet, Anna Cuomo, Oliver Stegle, et al.
Nature Biotechnology (2021) Vol. 39, Iss. 10, pp. 1202-1215
Closed Access | Times Cited: 334
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: 321
Genetic mapping of cell type specificity for complex traits
Kyoko Watanabe, Maša Umićević Mirkov, Christiaan de Leeuw, et al.
Nature Communications (2019) Vol. 10, Iss. 1
Open Access | Times Cited: 293
Quantitative single-cell proteomics as a tool to characterize cellular hierarchies
Erwin M. Schoof, Benjamin Furtwängler, Nil Üresin, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 288
Simultaneous profiling of 3D genome structure and DNA methylation in single human cells
Dong-Sung Lee, Chongyuan Luo, Jingtian Zhou, et al.
Nature Methods (2019) Vol. 16, Iss. 10, pp. 999-1006
Open Access | Times Cited: 269
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