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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:

iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data
Zhen Chen, Pei Zhao, Fuyi Li, et al.
Briefings in Bioinformatics (2019) Vol. 21, Iss. 3, pp. 1047-1057
Closed Access | Times Cited: 369

Showing 1-25 of 369 citing articles:

BioSeq-Analysis2.0: an updated platform for analyzing DNA, RNA and protein sequences at sequence level and residue level based on machine learning approaches
Bin Liu, Xin Gao, Hanyu Zhang
Nucleic Acids Research (2019) Vol. 47, Iss. 20, pp. e127-e127
Open Access | Times Cited: 351
Machine intelligence in peptide therapeutics: A next‐generation tool for rapid disease screening
Shaherin Basith, Balachandran Manavalan, Tae Hwan Shin, et al.
Medicinal Research Reviews (2020) Vol. 40, Iss. 4, pp. 1276-1314
Closed Access | Times Cited: 254
iLearnPlus:a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization
Zhen Chen, Pei Zhao, Chen Li, et al.
Nucleic Acids Research (2021) Vol. 49, Iss. 10, pp. e60-e60
Open Access | Times Cited: 195
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
HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation
Md Mehedi Hasan, Nalini Schaduangrat, Shaherin Basith, et al.
Bioinformatics (2020) Vol. 36, Iss. 11, pp. 3350-3356
Closed Access | Times Cited: 182
BioSeq-BLM: a platform for analyzing DNA, RNA and protein sequences based on biological language models
Hongliang Li, Yihe Pang, Bin Liu
Nucleic Acids Research (2021) Vol. 49, Iss. 22, pp. e129-e129
Open Access | Times Cited: 163
An Interpretable Prediction Model for Identifying N7-Methylguanosine Sites Based on XGBoost and SHAP
Yue Bi, Dongxu Xiang, Zongyuan Ge, et al.
Molecular Therapy — Nucleic Acids (2020) Vol. 22, pp. 362-372
Open Access | Times Cited: 138
Anticancer peptides prediction with deep representation learning features
Zhibin Lv, Feifei Cui, Quan Zou, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 5
Closed Access | Times Cited: 113
Comprehensive assessment of machine learning-based methods for predicting antimicrobial peptides
Jing Xu, Fuyi Li, André Leier, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 5
Closed Access | Times Cited: 112
DeepBIO: an automated and interpretable deep-learning platform for high-throughput biological sequence prediction, functional annotation and visualization analysis
Ruheng Wang, Yi Jiang, Junru Jin, et al.
Nucleic Acids Research (2023) Vol. 51, Iss. 7, pp. 3017-3029
Open Access | Times Cited: 98
BERT-Promoter: An improved sequence-based predictor of DNA promoter using BERT pre-trained model and SHAP feature selection
Nguyen Quoc Khanh Le, Quang‐Thai Ho, Van-Nui Nguyen, et al.
Computational Biology and Chemistry (2022) Vol. 99, pp. 107732-107732
Closed Access | Times Cited: 70
pAtbP-EnC: Identifying Anti-Tubercular Peptides Using Multi-Feature Representation and Genetic Algorithm-Based Deep Ensemble Model
Shahid Akbar, Ali Raza, Tamara Al Shloul, et al.
IEEE Access (2023) Vol. 11, pp. 137099-137114
Open Access | Times Cited: 53
m5U-SVM: identification of RNA 5-methyluridine modification sites based on multi-view features of physicochemical features and distributed representation
Chunyan Ao, Xiucai Ye, Tetsuya Sakurai, et al.
BMC Biology (2023) Vol. 21, Iss. 1
Open Access | Times Cited: 52
Sequence based model using deep neural network and hybrid features for identification of 5-hydroxymethylcytosine modification
Salman Khan, Islam Uddin, Mukhtaj Khan, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 16
AI Methods for Antimicrobial Peptides: Progress and Challenges
Carlos A. Brizuela, Gary Liu, J Stokes, et al.
Microbial Biotechnology (2025) Vol. 18, Iss. 1
Open Access | Times Cited: 2
Comprehensive review and assessment of computational methods for predicting RNA post-transcriptional modification sites from RNA sequences
Zhen Chen, Pei Zhao, Fuyi Li, et al.
Briefings in Bioinformatics (2019) Vol. 21, Iss. 5, pp. 1676-1696
Closed Access | Times Cited: 121
DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites
Quanzhong Liu, Jin-Xiang Chen, Yanze Wang, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Open Access | Times Cited: 113
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
DeepYY1: a deep learning approach to identify YY1-mediated chromatin loops
Fanny Dao, Hao Lv, Dan Zhang, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 4
Closed Access | Times Cited: 77
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
Deep4mC: systematic assessment and computational prediction for DNA N4-methylcytosine sites by deep learning
Haodong Xu, Peilin Jia, Zhongming Zhao
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Open Access | Times Cited: 73
STALLION: a stacking-based ensemble learning framework for prokaryotic lysine acetylation site prediction
Shaherin Basith, Gwang Lee, Balachandran Manavalan
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Open Access | Times Cited: 72
MathFeature: feature extraction package for DNA, RNA and protein sequences based on mathematical descriptors
Robson Parmezan Bonidia, Douglas Silva Domingues, Danilo Sipoli Sanches, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Open Access | Times Cited: 60
Pfeature: A Tool for Computing Wide Range of Protein Features and Building Prediction Models
Akshara Pande, Sumeet Patiyal, Anjali Lathwal, et al.
Journal of Computational Biology (2022) Vol. 30, Iss. 2, pp. 204-222
Closed Access | Times Cited: 59
iFeatureOmega:an integrative platform for engineering, visualization and analysis of features from molecular sequences, structural and ligand data sets
Zhen Chen, Xuhan Liu, Pei Zhao, et al.
Nucleic Acids Research (2022) Vol. 50, Iss. W1, pp. W434-W447
Open Access | Times Cited: 57
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