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:

Integrating regulatory DNA sequence and gene expression to predict genome-wide chromatin accessibility across cellular contexts
Surag Nair, Daniel Sunwook Kim, Jacob Perricone, et al.
Bioinformatics (2019) Vol. 35, Iss. 14, pp. i108-i116
Open Access | Times Cited: 69

Showing 1-25 of 69 citing articles:

Effective gene expression prediction from sequence by integrating long-range interactions
Žiga Avsec, Vikram Agarwal, Daniel Visentin, et al.
Nature Methods (2021) Vol. 18, Iss. 10, pp. 1196-1203
Open Access | Times Cited: 721
Systematic differences in discovery of genetic effects on gene expression and complex traits
Hakhamanesh Mostafavi, Jeffrey P. Spence, Sahin Naqvi, et al.
Nature Genetics (2023) Vol. 55, Iss. 11, pp. 1866-1875
Closed Access | Times Cited: 161
MVP predicts the pathogenicity of missense variants by deep learning
Hongjian Qi, Haicang Zhang, Yige Zhao, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 153
Limited overlap of eQTLs and GWAS hits due to systematic differences in discovery
Hakhamanesh Mostafavi, Jeffrey P. Spence, Sahin Naqvi, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 91
Prediction of histone post-translational modification patterns based on nascent transcription data
Zhong Wang, Alexandra G. Chivu, Lauren A. Choate, et al.
Nature Genetics (2022) Vol. 54, Iss. 3, pp. 295-305
Open Access | Times Cited: 81
Deep learning of immune cell differentiation
Alexandra Maslova, Ricardo N. Ramírez, Ke Ma, et al.
Proceedings of the National Academy of Sciences (2020) Vol. 117, Iss. 41, pp. 25655-25666
Open Access | Times Cited: 92
A survey on deep learning in DNA/RNA motif mining
Ying He, Zhen Shen, Qinhu Zhang, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 4
Open Access | Times Cited: 85
Decoding disease: from genomes to networks to phenotypes
Aaron K. Wong, Rachel Sealfon, Chandra L. Theesfeld, et al.
Nature Reviews Genetics (2021) Vol. 22, Iss. 12, pp. 774-790
Open Access | Times Cited: 71
Effective gene expression prediction from sequence by integrating long-range interactions
Žiga Avsec, Vikram Agarwal, Daniel Visentin, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 63
ChromBPNet: bias factorized, base-resolution deep learning models of chromatin accessibility reveal cis-regulatory sequence syntax, transcription factor footprints and regulatory variants
Anusri Pampari, Anna Shcherbina, Evgeny Z. Kvon, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 11
Recipes and ingredients for deep learning models of 3D genome folding
Paulina N. Smaruj, Yao Xiao, Geoffrey Fudenberg
Current Opinion in Genetics & Development (2025) Vol. 91, pp. 102308-102308
Open Access | Times Cited: 1
Interpretable detection of novel human viruses from genome sequencing data
Jakub M. Bartoszewicz, Anja Seidel, Bernhard Y. Renard
NAR Genomics and Bioinformatics (2021) Vol. 3, Iss. 1
Open Access | Times Cited: 52
MTSplice predicts effects of genetic variants on tissue-specific splicing
Jun Cheng, Muhammed Hasan Çelik, Anshul Kundaje, et al.
Genome biology (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 43
Genomics enters the deep learning era
Etienne Routhier, Julien Mozziconacci
PeerJ (2022) Vol. 10, pp. e13613-e13613
Open Access | Times Cited: 29
A pitfall for machine learning methods aiming to predict across cell types
Jacob Schreiber, Ritambhara Singh, Jeffrey A. Bilmes, et al.
Genome biology (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 45
Deep Learning Sequence Models for Transcriptional Regulation
Ksenia Sokolova, Kathleen Chen, Yun Hao, et al.
Annual Review of Genomics and Human Genetics (2024) Vol. 25, Iss. 1, pp. 105-122
Closed Access | Times Cited: 5
Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles
Huan Tao, Hao Li, Kang Xu, et al.
Briefings in Bioinformatics (2020)
Open Access | Times Cited: 28
GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership
Peter Carbonetto, Kaixuan Luo, Abhishek Sarkar, et al.
Genome biology (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 11
A multi-modal transformer for cell type-agnostic regulatory predictions
Nauman Javed, Thomas Weingarten, Arijit Sehanobish, et al.
Cell Genomics (2025), pp. 100762-100762
Open Access
NeuronMotif: Deciphering cis-regulatory codes by layer-wise demixing of deep neural networks
Wei Zheng, Kui Hua, Lei Wei, et al.
Proceedings of the National Academy of Sciences (2023) Vol. 120, Iss. 15
Open Access | Times Cited: 9
EpiGePT: a pretrained transformer-based language model for context-specific human epigenomics
Zijing Gao, Qiao Liu, Wanwen Zeng, et al.
Genome biology (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 3
DeepCAGE: Incorporating Transcription Factors in Genome-Wide Prediction of Chromatin Accessibility
Qiao Liu, Kui Hua, Xuegong Zhang, et al.
Genomics Proteomics & Bioinformatics (2022) Vol. 20, Iss. 3, pp. 496-507
Open Access | Times Cited: 14
Predictive analyses of regulatory sequences with EUGENe
Adam Klie, David Laub, James V. Talwar, et al.
Nature Computational Science (2023) Vol. 3, Iss. 11, pp. 946-956
Open Access | Times Cited: 8
EpiGePT: a Pretrained Transformer model for epigenomics
Zijing Gao, Qiao Liu, Wanwen Zeng, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 7
Prediction of G4 formation in live cells with epigenetic data: a deep learning approach
Anna Korsakova, Anh Tuân Phan
NAR Genomics and Bioinformatics (2023) Vol. 5, Iss. 3
Open Access | Times Cited: 7
Page 1 - Next Page

Scroll to top