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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:

Evaluating deep learning for predicting epigenomic profiles
Shushan Toneyan, Ziqi Tang, Peter K. Koo
Nature Machine Intelligence (2022) Vol. 4, Iss. 12, pp. 1088-1100
Open Access | Times Cited: 43

Showing 1-25 of 43 citing articles:

Cell-type-directed design of synthetic enhancers
Ibrahim Ihsan Taskiran, Katina I. Spanier, Hannah Dickmänken, et al.
Nature (2023) Vol. 626, Iss. 7997, pp. 212-220
Open Access | Times Cited: 66
Correcting gradient-based interpretations of deep neural networks for genomics
Antonio Majdandzic, Chandana Rajesh, Peter K. Koo
Genome biology (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 28
Evaluating the representational power of pre-trained DNA language models for regulatory genomics
Ziqi Tang, Nikunj V. Somia, Yiyang Yu, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 12
EvoAug: improving generalization and interpretability of genomic deep neural networks with evolution-inspired data augmentations
Nicholas Keone Lee, Ziqi Tang, Shushan Toneyan, et al.
Genome biology (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 20
Interpreting cis-regulatory mechanisms from genomic deep neural networks using surrogate models
E. Seitz, David M. McCandlish, Justin B. Kinney, et al.
Nature Machine Intelligence (2024) Vol. 6, Iss. 6, pp. 701-713
Closed Access | Times Cited: 7
Review of Computational Methods and Database Sources for Predicting the Effects of Coding Frameshift Small Insertion and Deletion Variations
Fang Ge, Muhammad Arif, Zihao Yan, et al.
ACS Omega (2024)
Open Access | Times Cited: 6
Towards in silico CLIP-seq: predicting protein-RNA interaction via sequence-to-signal learning
Marc Horlacher, Nils Wagner, Lambert Moyon, et al.
Genome biology (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 15
Iterative improvement of deep learning models using synthetic regulatory genomics
André M. Ribeiro-dos-Santos, Matthew T. Maurano
bioRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
Evaluation of deep learning approaches for high-resolution chromatin accessibility prediction from genomic sequence
Aayush Grover, Till Muser, Laura Kasak, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
Gauge fixing for sequence-function relationships
Anna Posfai, Juannan Zhou, David M. McCandlish, et al.
PLoS Computational Biology (2025) Vol. 21, Iss. 3, pp. e1012818-e1012818
Open Access
Integrative omics analysis reveals the genetic basis of fatty acid composition in Brassica napus seeds
Yuting Zhang, Yunhao Liu, Zhanxiang Zong, et al.
Research Square (Research Square) (2025)
Closed Access
Integrative omics analysis reveals the genetic basis of fatty acid composition in Brassica napus seeds
Yuting Zhang, Yunhao Liu, Zhanxiang Zong, et al.
Genome biology (2025) Vol. 26, Iss. 1
Open Access
Current genomic deep learning models display decreased performance in cell type-specific accessible regions
Pooja Kathail, Richard W. Shuai, Ryan Chung, et al.
Genome biology (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 4
Current approaches to genomic deep learning struggle to fully capture human genetic variation
Ziqi Tang, Shushan Toneyan, Peter K. Koo
Nature Genetics (2023) Vol. 55, Iss. 12, pp. 2021-2022
Closed Access | Times Cited: 9
Improving the performance of supervised deep learning for regulatory genomics using phylogenetic augmentation
Andrew Duncan, Jennifer A. Mitchell, Alan M Moses
Bioinformatics (2024) Vol. 40, Iss. 4
Open Access | Times Cited: 3
Gauge fixing for sequence-function relationships
Anna Posfai, Juannan Zhou, David M. McCandlish, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 3
Cross‐Species Prediction of Transcription Factor Binding by Adversarial Training of a Novel Nucleotide‐Level Deep Neural Network
Qinhu Zhang, Siguo Wang, Zhipeng Li, et al.
Advanced Science (2024)
Open Access | Times Cited: 3
Interpretingcis-regulatory mechanisms from genomic deep neural networks using surrogate models
E. Seitz, David M. McCandlish, Justin B. Kinney, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 8
Cross-species prediction of transcription factor binding by adversarial training of a novel nucleotide-level deep neural network
Qinhu Zhang
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 2
EvoAug-TF: extending evolution-inspired data augmentations for genomic deep learning to TensorFlow
Yiyang Yu, Shivani Muthukumar, Peter K. Koo
Bioinformatics (2024) Vol. 40, Iss. 3
Open Access | Times Cited: 2
Quantum mechanical electronic and geometric parameters for DNA k-mers as features for machine learning
Kairi Masuda, Adib Afandi Abdullah, Patrick Pflughaupt, et al.
Scientific Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 2
Predicting cell type-specific epigenomic profiles accounting for distal genetic effects
Alan E Murphy, William Beardall, Marek Rei, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Closed Access | Times Cited: 2
A fast machine learning dataloader for epigenetic tracks from BigWig files
Joren Sebastian Retel, Andreas Poehlmann, Joshua Chiou, et al.
Bioinformatics (2024) Vol. 40, Iss. 1
Open Access | Times Cited: 1
Comparative analysis of models in predicting the effects of SNPs on TF-DNA binding using large-scale in vitro and in vivo data
Dongmei Han, Yurun Li, Linxiao Wang, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 2
Open Access | Times Cited: 1
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