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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:

Improved prediction of protein–protein interactions using novel negative samples, features, and an ensemble classifier
Leyi Wei, Pengwei Xing, Jiancang Zeng, et al.
Artificial Intelligence in Medicine (2017) Vol. 83, pp. 67-74
Closed Access | Times Cited: 229

Showing 1-25 of 229 citing articles:

Machine learning approaches and databases for prediction of drug–target interaction: a survey paper
Maryam Bagherian, Elyas Sabeti, Kai Wang, et al.
Briefings in Bioinformatics (2019) Vol. 22, Iss. 1, pp. 247-269
Open Access | Times Cited: 334
Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways
Lei Chen, Yu-Hang Zhang, ShaoPeng Wang, et al.
PLoS ONE (2017) Vol. 12, Iss. 9, pp. e0184129-e0184129
Open Access | Times Cited: 332
AmPEP: Sequence-based prediction of antimicrobial peptides using distribution patterns of amino acid properties and random forest
Pratiti Bhadra, Jielu Yan, Jinyan Li, et al.
Scientific Reports (2018) Vol. 8, Iss. 1
Open Access | Times Cited: 247
Deep-Resp-Forest: A deep forest model to predict anti-cancer drug response
Ran Su, Xinyi Liu, Leyi Wei, et al.
Methods (2019) Vol. 166, pp. 91-102
Closed Access | Times Cited: 225
Prediction of human protein subcellular localization using deep learning
Leyi Wei, Yijie Ding, Ran Su, et al.
Journal of Parallel and Distributed Computing (2017) Vol. 117, pp. 212-217
Closed Access | Times Cited: 208
Meta-4mCpred: A Sequence-Based Meta-Predictor for Accurate DNA 4mC Site Prediction Using Effective Feature Representation
Balachandran Manavalan, Shaherin Basith, Tae Hwan Shin, et al.
Molecular Therapy — Nucleic Acids (2019) Vol. 16, pp. 733-744
Open Access | Times Cited: 199
CPPred-RF: A Sequence-based Predictor for Identifying Cell-Penetrating Peptides and Their Uptake Efficiency
Leyi Wei, Pengwei Xing, Ran Su, et al.
Journal of Proteome Research (2017) Vol. 16, Iss. 5, pp. 2044-2053
Closed Access | Times Cited: 192
Application of Machine Learning in Microbiology
Kaiyang Qu, Fei Guo, Xiangrong Liu, et al.
Frontiers in Microbiology (2019) Vol. 10
Open Access | Times Cited: 169
Clustering and classification methods for single-cell RNA-sequencing data
Ren Qi, Anjun Ma, Qin Ma, et al.
Briefings in Bioinformatics (2019) Vol. 21, Iss. 4, pp. 1196-1208
Open Access | Times Cited: 169
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
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: 103
A First Computational Frame for Recognizing Heparin-Binding Protein
Wen Zhu, Shi-Shi Yuan, Jian Li, et al.
Diagnostics (2023) Vol. 13, Iss. 14, pp. 2465-2465
Open Access | Times Cited: 66
Oral_voting_transfer: classification of oral microorganisms’ function proteins with voting transfer model
Wenzheng Bao, Yujun Liu, Baitong Chen
Frontiers in Microbiology (2024) Vol. 14
Open Access | Times Cited: 18
ACPred-Fuse: fusing multi-view information improves the prediction of anticancer peptides
B. Dharma Rao, Chen Zhou, Guoying Zhang, et al.
Briefings in Bioinformatics (2019) Vol. 21, Iss. 5, pp. 1846-1855
Closed Access | Times Cited: 142
SkipCPP-Pred: an improved and promising sequence-based predictor for predicting cell-penetrating peptides
Leyi Wei, Jijun Tang, Quan Zou
BMC Genomics (2017) Vol. 18, Iss. S7
Open Access | Times Cited: 123
A Novel Hybrid Sequence-Based Model for Identifying Anticancer Peptides
Lei Xu, Guangmin Liang, Longjie Wang, et al.
Genes (2018) Vol. 9, Iss. 3, pp. 158-158
Open Access | Times Cited: 107
A Random Forest Sub-Golgi Protein Classifier Optimized via Dipeptide and Amino Acid Composition Features
Zhibin Lv, Shunshan Jin, Hui Ding, et al.
Frontiers in Bioengineering and Biotechnology (2019) Vol. 7
Open Access | Times Cited: 106
An Efficient Classifier for Alzheimer’s Disease Genes Identification
Lei Xu, Guangmin Liang, Changrui Liao, et al.
Molecules (2018) Vol. 23, Iss. 12, pp. 3140-3140
Open Access | Times Cited: 102
iRNA-m7G: Identifying N7-methylguanosine Sites by Fusing Multiple Features
Wei Chen, Pengmian Feng, Xiaoming Song, et al.
Molecular Therapy — Nucleic Acids (2019) Vol. 18, pp. 269-274
Open Access | Times Cited: 94
A Novel Modeling in Mathematical Biology for Classification of Signal Peptides
Asma Ehsan, Khalid Mahmood, Yaser Daanial Khan, et al.
Scientific Reports (2018) Vol. 8, Iss. 1
Open Access | Times Cited: 84
Gradient Boosting Decision Tree-Based Method for Predicting Interactions Between Target Genes and Drugs
Ping Xuan, Chang Sun, Tiangang Zhang, et al.
Frontiers in Genetics (2019) Vol. 10
Open Access | Times Cited: 80
Classification and prediction of protein–protein interaction interface using machine learning algorithm
Subhrangshu Das, Saikat Chakrabarti
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 80
Incorporating Distance-Based Top-n-gram and Random Forest To Identify Electron Transport Proteins
Xiaoqing Ru, Lihong Li, Quan Zou
Journal of Proteome Research (2019) Vol. 18, Iss. 7, pp. 2931-2939
Closed Access | Times Cited: 79
RF-PseU: A Random Forest Predictor for RNA Pseudouridine Sites
Zhibin Lv, Jun Zhang, Hui Ding, et al.
Frontiers in Bioengineering and Biotechnology (2020) Vol. 8
Open Access | Times Cited: 79
k-Skip-n-Gram-RF: A Random Forest Based Method for Alzheimer's Disease Protein Identification
Lei Xu, Guangmin Liang, Changrui Liao, et al.
Frontiers in Genetics (2019) Vol. 10
Open Access | Times Cited: 76
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