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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.

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Showing 1-25 of 356 citing articles:

ProtGPT2 is a deep unsupervised language model for protein design
Noelia Ferruz, Steffen Schmidt, Birte Höcker
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 423
Distance-based Support Vector Machine to Predict DNA N6- methyladenine Modification
Haoyu Zhang, Quan Zou, Ying Ju, et al.
Current Bioinformatics (2022) Vol. 17, Iss. 5, pp. 473-482
Closed Access | Times Cited: 298
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: 199
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: 171
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: 141
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: 119
SBSM-Pro: support bio-sequence machine for proteins
Yizheng Wang, Yixiao Zhai, Yijie Ding, et al.
Science China Information Sciences (2024) Vol. 67, Iss. 11
Closed Access | Times Cited: 118
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: 104
MLCPP 2.0: An Updated Cell-penetrating Peptides and Their Uptake Efficiency Predictor
Balachandran Manavalan, Mahesh Chandra Patra
Journal of Molecular Biology (2022) Vol. 434, Iss. 11, pp. 167604-167604
Closed Access | Times Cited: 73
Biological Sequence Classification: A Review on Data and General Methods
Chunyan Ao, Shihu Jiao, Yansu Wang, et al.
Research (2022) Vol. 2022
Open Access | Times Cited: 73
BioSeq-Diabolo: Biological sequence similarity analysis using Diabolo
Hongliang Li, Bin Liu
PLoS Computational Biology (2023) Vol. 19, Iss. 6, pp. e1011214-e1011214
Open Access | Times Cited: 66
DeepSVM-fold: protein fold recognition by combining support vector machines and pairwise sequence similarity scores generated by deep learning networks
Bin Liu, Chenchen Li, Ke Yan
Briefings in Bioinformatics (2019) Vol. 21, Iss. 5, pp. 1733-1741
Closed Access | Times Cited: 144
Design powerful predictor for mRNA subcellular location prediction inHomo sapiens
Zhao‐Yue Zhang, Yuhe R. Yang, Hui Ding, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 1, pp. 526-535
Open Access | Times Cited: 125
sgRNACNN: identifying sgRNA on-target activity in four crops using ensembles of convolutional neural networks
Mengting Niu, Yuan Lin, Quan Zou
Plant Molecular Biology (2021) Vol. 105, Iss. 4-5, pp. 483-495
Closed Access | Times Cited: 105
An in silico approach to identification, categorization and prediction of nucleic acid binding proteins
Lei Xu, Shanshan Jiang, Jin Wu, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Open Access | Times Cited: 87
Computational identification of N6-methyladenosine sites in multiple tissues of mammals
Fanny Dao, Hao Lv, Yuhe R. Yang, et al.
Computational and Structural Biotechnology Journal (2020) Vol. 18, pp. 1084-1091
Open Access | Times Cited: 84
DeepM6ASeq-EL: prediction of human N6-methyladenosine (m6A) sites with LSTM and ensemble learning
Juntao Chen, Quan Zou, Jing Li
Frontiers of Computer Science (2021) Vol. 16, Iss. 2
Closed Access | Times Cited: 80
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: 74
Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy
Md Mehedi Hasan, Sho Tsukiyama, Jae Youl Cho, et al.
Molecular Therapy (2022) Vol. 30, Iss. 8, pp. 2856-2867
Open Access | Times Cited: 66
iAMP-CA2L: a new CNN-BiLSTM-SVM classifier based on cellular automata image for identifying antimicrobial peptides and their functional types
Xuan Xiao, Yutao Shao, Xiang Cheng, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Closed Access | Times Cited: 65
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: 63
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: 62
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: 59
iPro-WAEL: a comprehensive and robust framework for identifying promoters in multiple species
Pengyu Zhang, Hongming Zhang, Hao Wu
Nucleic Acids Research (2022) Vol. 50, Iss. 18, pp. 10278-10289
Open Access | Times Cited: 57
MLACP 2.0: An updated machine learning tool for anticancer peptide prediction
Le Thi Phan, Hyun Woo Park, Thejkiran Pitti, et al.
Computational and Structural Biotechnology Journal (2022) Vol. 20, pp. 4473-4480
Open Access | Times Cited: 50
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