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:

Multi-task learning from multimodal single-cell omics with Matilda
Chunlei Liu, Hao Huang, Pengyi Yang
Nucleic Acids Research (2023) Vol. 51, Iss. 8, pp. e45-e45
Open Access | Times Cited: 16

Showing 16 citing articles:

Gene regulatory network reconstruction: harnessing the power of single-cell multi-omic data
Daniel Kim, Andy Tran, Hani Jieun Kim, et al.
npj Systems Biology and Applications (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 32

Applying interpretable machine learning in computational biology—pitfalls, recommendations and opportunities for new developments
Valerie Chen, Muyu Yang, Wenbo Cui, et al.
Nature Methods (2024) Vol. 21, Iss. 8, pp. 1454-1461
Closed Access | Times Cited: 11

Evaluation of deep learning-based feature selection for single-cell RNA sequencing data analysis
Hao Huang, Chunlei Liu, Manoj M Wagle, et al.
Genome biology (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 14

Multimodal hierarchical classification of CITE-seq data delineates immune cell states across lineages and tissues
Daniel P. Caron, William L. Specht, David Chen, et al.
Cell Reports Methods (2025), pp. 100938-100938
Open Access

Recent advances in exploring transcriptional regulatory landscape of crops
Qiang Huo, Rentao Song, Zeyang Ma
Frontiers in Plant Science (2024) Vol. 15
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

Ensemble deep learning of embeddings for clustering multimodal single-cell omics data
Lijia Yu, Chunlei Liu, Jean Yang, et al.
Bioinformatics (2023) Vol. 39, Iss. 6
Open Access | Times Cited: 7

scMoMtF: An interpretable multitask learning framework for single-cell multi-omics data analysis
Wei Lan, T. Y. Ling, Qingfeng Chen, et al.
PLoS Computational Biology (2024) Vol. 20, Iss. 12, pp. e1012679-e1012679
Open Access | Times Cited: 2

scMHNN: a novel hypergraph neural network for integrative analysis of single-cell epigenomic, transcriptomic and proteomic data
Wei Li, Bin Xiang, Fan Yang, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 6
Closed Access | Times Cited: 3

A Message Passing Framework for Precise Cell State Identification with scClassify2
Wenze Ding, Yue Cao, Xiaohang Fu, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Closed Access

CSIP: Contrastive learning with Graph Neural Network enables chemical structure to image mapping
Chengxi Liu
Applied and Computational Engineering (2024) Vol. 86, Iss. 1, pp. 301-313
Open Access

CLUEY enables knowledge-guided clustering and cell type detection from single-cell omics data
Daniel Kim, Carissa Chen, Lijia Yu, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access

Ocelli: an open-source tool for the visualization of developmental multimodal single-cell data
Piotr Rutkowski, Marcin Tabaka
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access

UMINT-FS: UMINT-guided Feature Selection for multi-omics datasets
Chayan Maitra, Dibyendu Bikash Seal, Vivek Das, et al.
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2023), pp. 594-601
Closed Access

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