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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:

DeepPhos: prediction of protein phosphorylation sites with deep learning
Fenglin Luo, Minghui Wang, Yu Liu, et al.
Bioinformatics (2018) Vol. 35, Iss. 16, pp. 2766-2773
Open Access | Times Cited: 166

Showing 1-25 of 166 citing articles:

MusiteDeep: a deep-learning based webserver for protein post-translational modification site prediction and visualization
Duolin Wang, Dongpeng Liu, Jiakang Yuchi, et al.
Nucleic Acids Research (2020) Vol. 48, Iss. W1, pp. W140-W146
Open Access | Times Cited: 204
Deep Learning in Protein Structural Modeling and Design
Wenhao Gao, Sai Pooja Mahajan, Jeremias Sulam, et al.
Patterns (2020) Vol. 1, Iss. 9, pp. 100142-100142
Open Access | Times Cited: 184
Machine learning meets omics: applications and perspectives
Rufeng Li, Lixin Li, Yungang Xu, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Closed Access | Times Cited: 112
The deep learning applications in IoT-based bio- and medical informatics: a systematic literature review
Zahra Mohtasham‐Amiri, Arash Heidari, Nima Jafari Navimipour, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 11, pp. 5757-5797
Open Access | Times Cited: 52
Deep Learning in Proteomics
Bo Wen, Wen‐Feng Zeng, Yuxing Liao, et al.
PROTEOMICS (2020) Vol. 20, Iss. 21-22
Open Access | Times Cited: 127
DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites
Fuyi Li, Jin-Xiang Chen, André Leier, et al.
Bioinformatics (2019) Vol. 36, Iss. 4, pp. 1057-1065
Open Access | Times Cited: 107
Incorporating Machine Learning into Established Bioinformatics Frameworks
Noam Auslander, Ayal B. Gussow, Eugene V. Koonin
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 6, pp. 2903-2903
Open Access | Times Cited: 85
Using deep neural networks and biological subwords to detect protein S-sulfenylation sites
Duyen Thi, Thanh Quynh Trang Le, Nguyen Quoc Khanh Le
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Closed Access | Times Cited: 84
Feature selection may improve deep neural networks for the bioinformatics problems
Zheng Chen, Meng Pang, Zixin Zhao, et al.
Bioinformatics (2019) Vol. 36, Iss. 5, pp. 1542-1552
Open Access | Times Cited: 83
DeepIPs: comprehensive assessment and computational identification of phosphorylation sites of SARS-CoV-2 infection using a deep learning-based approach
Hao Lv, Fanny Dao, Hasan Zulfiqar, et al.
Briefings in Bioinformatics (2021)
Open Access | Times Cited: 77
Applications of deep learning in understanding gene regulation
Zhongxiao Li, Elva Gao, Juexiao Zhou, et al.
Cell Reports Methods (2023) Vol. 3, Iss. 1, pp. 100384-100384
Open Access | Times Cited: 27
Combining machine learning with structure-based protein design to predict and engineer post-translational modifications of proteins
Moritz Ertelt, Vikram Khipple Mulligan, Jack B. Maguire, et al.
PLoS Computational Biology (2024) Vol. 20, Iss. 3, pp. e1011939-e1011939
Open Access | Times Cited: 11
Deep learning for mining protein data
Qiang Shi, Weiya Chen, Siqi Huang, et al.
Briefings in Bioinformatics (2019) Vol. 22, Iss. 1, pp. 194-218
Closed Access | Times Cited: 67
Optimization of serine phosphorylation prediction in proteins by comparing human engineered features and deep representations
Sheraz Naseer, Waqar Hussain, Yaser Daanial Khan, et al.
Analytical Biochemistry (2020) Vol. 615, pp. 114069-114069
Closed Access | Times Cited: 58
DeepSuccinylSite: a deep learning based approach for protein succinylation site prediction
Niraj Thapa, Meenal Chaudhari, Sean McManus, et al.
BMC Bioinformatics (2020) Vol. 21, Iss. S3
Open Access | Times Cited: 57
PhosIDN: an integrated deep neural network for improving protein phosphorylation site prediction by combining sequence and protein–protein interaction information
Hangyuan Yang, Minghui Wang, Xia Liu, et al.
Bioinformatics (2021) Vol. 37, Iss. 24, pp. 4668-4676
Open Access | Times Cited: 52
StackPDB: Predicting DNA-binding proteins based on XGB-RFE feature optimization and stacked ensemble classifier
Qingmei Zhang, Peishun Liu, Xue Wang, et al.
Applied Soft Computing (2020) Vol. 99, pp. 106921-106921
Open Access | Times Cited: 51
iPhosS(Deep)-PseAAC: Identify Phosphoserine Sites in Proteins using Deep Learning on General Pseudo Amino Acid Compositions via Modified 5-Steps Rule
Sheraz Naseer, Waqar Hussain, Yaser Daanial Khan, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2020) Vol. 19, Iss. 3, pp. 1703-1714
Closed Access | Times Cited: 50
A review on recent trends in the phosphoproteomics workflow. From sample preparation to data analysis
Jiřı́ Urban
Analytica Chimica Acta (2021) Vol. 1199, pp. 338857-338857
Closed Access | Times Cited: 47
Mini-review: Recent advances in post-translational modification site prediction based on deep learning
Lingkuan Meng, Wai‐Sum Chan, Lei Huang, et al.
Computational and Structural Biotechnology Journal (2022) Vol. 20, pp. 3522-3532
Open Access | Times Cited: 31
KinasePhos 3.0: Redesign and Expansion of the Prediction on Kinase-Specific Phosphorylation Sites
Renfei Ma, Shangfu Li, Wenshuo Li, et al.
Genomics Proteomics & Bioinformatics (2022) Vol. 21, Iss. 1, pp. 228-241
Open Access | Times Cited: 29
LMPhosSite: A Deep Learning-Based Approach for General Protein Phosphorylation Site Prediction Using Embeddings from the Local Window Sequence and Pretrained Protein Language Model
Subash C. Pakhrin, Suresh Pokharel, Pawel Pratyush, et al.
Journal of Proteome Research (2023) Vol. 22, Iss. 8, pp. 2548-2557
Closed Access | Times Cited: 20
Advancing the accuracy of SARS-CoV-2 phosphorylation site detection via meta-learning approach
Nhat Truong Pham, Le Thi Phan, Ji-Min Seo, et al.
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 20
Advances in the Applications of Bioinformatics and Chemoinformatics
Mohamed A. Raslan, Sara A. Raslan, Eslam M. Shehata, et al.
Pharmaceuticals (2023) Vol. 16, Iss. 7, pp. 1050-1050
Open Access | Times Cited: 17
A Review of Machine Learning and Algorithmic Methods for Protein Phosphorylation Site Prediction
Farzaneh Esmaili, Mahdi Pourmirzaei, Shahin Ramazi, et al.
Genomics Proteomics & Bioinformatics (2023) Vol. 21, Iss. 6, pp. 1266-1285
Open Access | Times Cited: 17
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