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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:

siVAE: interpretable deep generative models for single-cell transcriptomes
Yongin Choi, Ruoxin Li, Gerald Quon
Genome biology (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 25

Showing 25 citing articles:

BuDDI: Bulk Deconvolution with Domain Invariance to predict cell-type-specific perturbations from bulk
Natalie R. Davidson, Fan Zhang, Casey S. Greene
PLoS Computational Biology (2025) Vol. 21, Iss. 1, pp. e1012742-e1012742
Open Access
Infusing structural assumptions into dimensionality reduction for single-cell RNA sequencing data to identify small gene sets
Maren Hackenberg, Niklas Brunn, Tanja Vogel, et al.
Communications Biology (2025) Vol. 8, Iss. 1
Open Access
Towards the Next Generation of Data‐Driven Therapeutics Using Spatially Resolved Single‐Cell Technologies and Generative AI
Avital Rodov, Hosna Baniadam, Robert Zeiser, et al.
European Journal of Immunology (2025) Vol. 55, Iss. 2
Open Access
Interpretable single-cell factor decomposition using sciRED
Delaram Pouyabahar, Tallulah Andrews, Gary D. Bader
Nature Communications (2025) Vol. 16, Iss. 1
Open Access
scBiG for representation learning of single-cell gene expression data based on bipartite graph embedding
Ting Li, Kun Qian, Xiang Wang, et al.
NAR Genomics and Bioinformatics (2024) Vol. 6, Iss. 1
Open Access | Times Cited: 3
Interpretable deep learning in single-cell omics
Manoj M Wagle, Siqu Long, Carissa Chen, et al.
Bioinformatics (2024) Vol. 40, Iss. 6
Open Access | Times Cited: 3
Infusing structural assumptions into dimension reduction for single-cell RNA sequencing data to identify small gene sets
Maren Hackenberg, Niklas Brunn, Tanja Vogel, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 2
GTM-decon: guided-topic modeling of single-cell transcriptomes enables sub-cell-type and disease-subtype deconvolution of bulk transcriptomes
Lakshmipuram S. Swapna, Michael Huang, Yue Li
Genome biology (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 6
Graph attention autoencoder model with dual decoder for clustering single-cell RNA sequencing data
Shudong Wang, Y. Zhang, Yuanyuan Zhang, et al.
Applied Intelligence (2024) Vol. 54, Iss. 6, pp. 5136-5146
Closed Access | Times Cited: 1
Interpretable single-cell factor decomposition using sciRED
Delaram Pouyabahar, Tallulah Andrews, Gary D. Bader
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
scPair: Boosting single cell multimodal analysis by leveraging implicit feature selection and single cell atlases
Hongru Hu, Gerald Quon
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 1
scAce: an adaptive embedding and clustering method for single-cell gene expression data
Xinwei He, Kun Qian, Ziqian Wang, et al.
Bioinformatics (2023) Vol. 39, Iss. 9
Open Access | Times Cited: 4
MOSim: bulk and single-cell multi-layer regulatory network simulator
Carolina Monzó, Maider Aguerralde‐Martin, Carlos Martínez-Mira, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2018)
Open Access | Times Cited: 11
NCAE: data-driven representations using a deep network-coherent DNA methylation autoencoder identify robust disease and risk factor signatures
David Martínez-Enguita, Sanjiv K. Dwivedi, Rebecka Jörnsten, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 5
Open Access | Times Cited: 2
Model-based evaluation of spatiotemporal data reduction methods with unknown ground truth through optimal visualization and interpretability metrics
Komlan Atitey, Alison A. Motsinger‐Reif, Benedict Anchang
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 2
Comprehensive single-cell RNA-seq analysis using deep interpretable generative modeling guided by biological hierarchy knowledge
Hegang Chen, Yuyin Lu, Zhiming Dai, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 4
Open Access
Interpretable single-cell factor decomposition using sciRED
Gary D. Bader, Delaram Pouyabahar, Tallulah Andrews
Research Square (Research Square) (2024)
Open Access
LCL: Contrastive Learning for Lineage Barcoded scRNA-seq Data
S.-N. Yang, Zhaoran Wang, Kevin Lin
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Towards virtual sample generation with various data conditions: A comprehensive review
Yi Jiang, Xiaoyuan Ma, Xiong Li
Information Fusion (2024), pp. 102874-102874
Closed Access
scGraph2Vec: a deep generative model for gene embedding augmented by graph neural network and single-cell omics data
Shiqi Lin, Peilin Jia
GigaScience (2024) Vol. 13
Open Access
Mapping the gene space at single-cell resolution with gene signal pattern analysis
Aarthi Venkat, Sam Leone, Scott E. Youlten, et al.
Nature Computational Science (2024) Vol. 4, Iss. 12, pp. 955-977
Closed Access
BuDDI:Bulk Deconvolution with Domain Invarianceto predict cell-type-specific perturbations from bulk
Natalie R. Davidson, Fan Zhang, Casey S. Greene
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 1
Geometric Quantification of Cell Phenotype Transition Manifolds with Information Geometry
Miao Huang, Junda Ying, Yuxuan Wang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access
Guided-topic modelling of single-cell transcriptomes enables sub-cell-type and disease-subtype deconvolution of bulk transcriptomes
Lakshmipuram S. Swapna, Michael Huang, Yue Li
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access
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