Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

RNA velocity—current challenges and future perspectives
Volker Bergen, Ruslan Soldatov, Peter V. Kharchenko, et al.
Molecular Systems Biology (2021) Vol. 17, Iss. 8
Open Access | Times Cited: 209

Showing 1-25 of 209 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: 506
Mapping transcriptomic vector fields of single cells
Xiaojie Qiu, Yan Zhang, Jorge D. Martin-Rufino, et al.
Cell (2022) Vol. 185, Iss. 4, pp. 690-711.e45
Open Access | Times Cited: 296
Functional roles of reactive astrocytes in neuroinflammation and neurodegeneration
Rickie Patani, Giles E. Hardingham, Shane A. Liddelow
Nature Reviews Neurology (2023) Vol. 19, Iss. 7, pp. 395-409
Closed Access | Times Cited: 233
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: 117
Computational solutions for spatial transcriptomics
Iivari Kleino, Paulina Frolovaitė, Tomi Suomi, et al.
Computational and Structural Biotechnology Journal (2022) Vol. 20, pp. 4870-4884
Open Access | Times Cited: 83
UniTVelo: temporally unified RNA velocity reinforces single-cell trajectory inference
Mingze Gao, Chen Qiao, Yuanhua Huang
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 73
Multi-omic single-cell velocity models epigenome–transcriptome interactions and improves cell fate prediction
Chen Li, Maria Virgilio, Kathleen L. Collins, et al.
Nature Biotechnology (2022) Vol. 41, Iss. 3, pp. 387-398
Open Access | Times Cited: 71
A reference cell tree will serve science better than a reference cell atlas
Silvia Domcke, Jay Shendure
Cell (2023) Vol. 186, Iss. 6, pp. 1103-1114
Closed Access | Times Cited: 66
A relay velocity model infers cell-dependent RNA velocity
Shengyu Li, Pengzhi Zhang, Weiqing Chen, et al.
Nature Biotechnology (2023) Vol. 42, Iss. 1, pp. 99-108
Open Access | Times Cited: 61
Biologically informed deep learning to query gene programs in single-cell atlases
Mohammad Lotfollahi, Sergei Rybakov, Karin Hrovatin, et al.
Nature Cell Biology (2023)
Open Access | Times Cited: 57
Inference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets
Shilu Zhang, Saptarshi Pyne, Stefan Pietrzak, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 56
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: 55
Zebrahub – Multimodal Zebrafish Developmental Atlas Reveals the State-Transition Dynamics of Late-Vertebrate Pluripotent Axial Progenitors
Merlin Lange, Alejandro Granados, Shruthi VijayKumar, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 54
Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells
Adam Gayoso, Philipp Weiler, Mohammad Lotfollahi, et al.
Nature Methods (2023) Vol. 21, Iss. 1, pp. 50-59
Open Access | Times Cited: 50
Lineage-specific intolerance to oncogenic drivers restricts histological transformation
Eric E. Gardner, Ethan M. Earlie, Kate Li, et al.
Science (2024) Vol. 383, Iss. 6683
Open Access | Times Cited: 33
CellRank 2: unified fate mapping in multiview single-cell data
Philipp Weiler, Marius Lange, Michal Klein, et al.
Nature Methods (2024) Vol. 21, Iss. 7, pp. 1196-1205
Open Access | Times Cited: 30
DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kinetics
Haotian Cui, Hassaan Maan, Maria C. Vladoiu, et al.
Genome biology (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 23
Transcription–replication interactions reveal bacterial genome regulation
Andrew W. Pountain, Peien Jiang, Tianyou Yao, et al.
Nature (2024) Vol. 626, Iss. 7999, pp. 661-669
Open Access | Times Cited: 21
Data analysis guidelines for single-cell RNA-seq in biomedical studies and clinical applications
Min‐Ying Su, Tao Pan, Qiu-Zhen Chen, et al.
Military Medical Research (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 59
Two subsets of human marginal zone B cells resolved by global analysis of lymphoid tissues and blood
Jacqueline H.Y. Siu, Michael J. Pitcher, Thomas J. Tull, et al.
Science Immunology (2022) Vol. 7, Iss. 69
Open Access | Times Cited: 49
Ushering in a new era of single-cell transcriptomics in bacteria
Christina Homberger, Lars Barquist, Jörg Vogel
microLife (2022) Vol. 3
Open Access | Times Cited: 44
Single-cell and single-nuclei RNA sequencing as powerful tools to decipher cellular heterogeneity and dysregulation in neurodegenerative diseases
Raquel Cuevas‐Díaz Durán, Juan Carlos González-Orozco, Iván Velasco, et al.
Frontiers in Cell and Developmental Biology (2022) Vol. 10
Open Access | Times Cited: 38
Pumping the brakes on RNA velocity by understanding and interpreting RNA velocity estimates
Shijie Zheng, Genevieve Stein-O’Brien, Leandros Boukas, et al.
Genome biology (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 33
PhyloVelo enhances transcriptomic velocity field mapping using monotonically expressed genes
Kun Wang, Liangzhen Hou, Xin Wang, et al.
Nature Biotechnology (2023) Vol. 42, Iss. 5, pp. 778-789
Open Access | Times Cited: 31
Page 1 - Next Page

Scroll to top