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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:

PredGly: predicting lysine glycation sites for Homo sapiens based on XGboost feature optimization
Jialin Yu, Shaoping Shi, Fang Zhang, et al.
Bioinformatics (2018) Vol. 35, Iss. 16, pp. 2749-2756
Closed Access | Times Cited: 64

Showing 1-25 of 64 citing articles:

Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier
Cheng Chen, Qingmei Zhang, Bin Yu, et al.
Computers in Biology and Medicine (2020) Vol. 123, pp. 103899-103899
Closed Access | Times Cited: 194
SDM6A: A Web-Based Integrative Machine-Learning Framework for Predicting 6mA Sites in the Rice Genome
Shaherin Basith, Balachandran Manavalan, Tae Hwan Shin, et al.
Molecular Therapy — Nucleic Acids (2019) Vol. 18, pp. 131-141
Open Access | Times Cited: 151
Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering
Sami Ben Jabeur, Nicolae Stef, Pedro Carmona
Computational Economics (2022) Vol. 61, Iss. 2, pp. 715-741
Closed Access | Times Cited: 101
iMRM: a platform for simultaneously identifying multiple kinds of RNA modifications
Kewei Liu, Wei Chen
Bioinformatics (2020) Vol. 36, Iss. 11, pp. 3336-3342
Open Access | Times Cited: 136
Meta-i6mA: an interspecies predictor for identifying DNAN6-methyladenine sites of plant genomes by exploiting informative features in an integrative machine-learning framework
Md Mehedi Hasan, Shaherin Basith, Mst. Shamima Khatun, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Closed Access | Times Cited: 113
Deep-Kcr: accurate detection of lysine crotonylation sites using deep learning method
Hao Lv, Fanny Dao, Zheng-Xing Guan, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 4
Closed Access | Times Cited: 112
PASSION: an ensemble neural network approach for identifying the binding sites of RBPs on circRNAs
Cangzhi Jia, Yue Bi, Jin-Xiang Chen, et al.
Bioinformatics (2020) Vol. 36, Iss. 15, pp. 4276-4282
Open Access | Times Cited: 74
Prediction of three-phase product distribution and bio-oil heating value of biomass fast pyrolysis based on machine learning
Erwei Leng, Ben He, Jingwei Chen, et al.
Energy (2021) Vol. 236, pp. 121401-121401
Closed Access | Times Cited: 59
Prediction of protein crotonylation sites through LightGBM classifier based on SMOTE and elastic net
Yaning Liu, Zhaomin Yu, Cheng Chen, et al.
Analytical Biochemistry (2020) Vol. 609, pp. 113903-113903
Closed Access | Times Cited: 69
Computational prediction and interpretation of both general and specific types of promoters in Escherichia coli by exploiting a stacked ensemble-learning framework
Fuyi Li, Jin-Xiang Chen, Zongyuan Ge, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 2, pp. 2126-2140
Open Access | Times Cited: 68
DeepVF: a deep learning-based hybrid framework for identifying virulence factors using the stacking strategy
Ruopeng Xie, Jiahui Li, Jiawei Wang, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Open Access | Times Cited: 59
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
Deep learning and ensemble deep learning for circRNA-RBP interaction prediction in the last decade: A review
Dilan Lasantha, Sugandima Vidanagamachchi, Sam Nallaperuma
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106352-106352
Closed Access | Times Cited: 19
A new FCM-XGBoost system for predicting Pavement Condition Index
Lin Lin, Shengnan Li, Kaipeng Wang, et al.
Expert Systems with Applications (2024) Vol. 249, pp. 123696-123696
Closed Access | Times Cited: 7
nhKcr: a new bioinformatics tool for predicting crotonylation sites on human nonhistone proteins based on deep learning
Yongzi Chen, Zhuozhi Wang, Yanan Wang, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Open Access | Times Cited: 39
A comprehensive review of the imbalance classification of protein post-translational modifications
Lijun Dou, Fenglong Yang, Lei Xu, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 5
Closed Access | Times Cited: 36
A hybrid XGBoost-ISSA-LSTM model for accurate short-term and long-term dissolved oxygen prediction in ponds
Yuhan Wu, Longqing Sun, Xibei Sun, et al.
Environmental Science and Pollution Research (2021) Vol. 29, Iss. 12, pp. 18142-18159
Closed Access | Times Cited: 36
Machine learning prediction of physical properties and nitrogen content of porous carbon from agricultural wastes: Effects of activation and doping process
Xiaohua Li, Ziheng Huang, Shanshan Shao, et al.
Fuel (2023) Vol. 356, pp. 129623-129623
Closed Access | Times Cited: 15
Factors related to steroid treatment responsiveness in thyroid eye disease patients and application of SHAP for feature analysis with XGBoost
Jungyul Park, Jae Hyun Kim, Dongman Ryu, et al.
Frontiers in Endocrinology (2023) Vol. 14
Open Access | Times Cited: 13
Machine Learning Enables Accurate Prediction of Asparagine Deamidation Probability and Rate
Jared A. Delmar, Jihong Wang, Seo Woo Choi, et al.
Molecular Therapy — Methods & Clinical Development (2019) Vol. 15, pp. 264-274
Open Access | Times Cited: 41
DeepPPSite: A deep learning-based model for analysis and prediction of phosphorylation sites using efficient sequence information
Saeed Ahmed, Muhammad Kabir, Muhammad Arif, et al.
Analytical Biochemistry (2020) Vol. 612, pp. 113955-113955
Closed Access | Times Cited: 35
SulSite-GTB: identification of protein S-sulfenylation sites by fusing multiple feature information and gradient tree boosting
Minghui Wang, Xiaoqiang Cui, Bin Yu, et al.
Neural Computing and Applications (2020) Vol. 32, Iss. 17, pp. 13843-13862
Closed Access | Times Cited: 33
Prediction of Maize Phenotypic Traits With Genomic and Environmental Predictors Using Gradient Boosting Frameworks
Cathy Westhues, Gregory S. Mahone, Sofia Da Silva, et al.
Frontiers in Plant Science (2021) Vol. 12
Open Access | Times Cited: 31
Staem5: A novel computational approach for accurate prediction of m5C site
Di Chai, Cangzhi Jia, Jia Zheng, et al.
Molecular Therapy — Nucleic Acids (2021) Vol. 26, pp. 1027-1034
Open Access | Times Cited: 23
A novel stacking-based predictor for accurate prediction of antimicrobial peptides
Sameera Kanwal, Roha Arif, Saeed Ahmed, et al.
Journal of Biomolecular Structure and Dynamics (2024), pp. 1-12
Closed Access | Times Cited: 3
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