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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:

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

Showing 1-25 of 113 citing articles:

Prediction of anticancer peptides based on an ensemble model of deep learning and machine learning using ordinal positional encoding
Qitong Yuan, Keyi Chen, Yimin Yu, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 1
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: 70
UniKP: a unified framework for the prediction of enzyme kinetic parameters
Han Yu, Huaxiang Deng, Jiahui He, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 62
Anti-Cancer Peptides: Status and Future Prospects
Gehane Ghaly, Hatem Tallima, Eslam Dabbish, et al.
Molecules (2023) Vol. 28, Iss. 3, pp. 1148-1148
Open Access | Times Cited: 42
iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities
Jing Xu, Fuyi Li, Chen Li, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 4
Open Access | Times Cited: 40
StackedEnC-AOP: prediction of antioxidant proteins using transform evolutionary and sequential features based multi-scale vector with stacked ensemble learning
Gul Rukh, Shahid Akbar, Gauhar Rehman, et al.
BMC Bioinformatics (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 25
SYNBIP: synthetic binding proteins for research, diagnosis and therapy
Xiaona Wang, Fengcheng Li, Wenqi Qiu, et al.
Nucleic Acids Research (2021) Vol. 50, Iss. D1, pp. D560-D570
Open Access | Times Cited: 64
Bitter-RF: A random forest machine model for recognizing bitter peptides
Yufei Zhang, Yuhao Wang, Zhi-Feng Gu, et al.
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 40
Machine Learning–Based Prediction of Acute Kidney Injury Following Pediatric Cardiac Surgery: Model Development and Validation Study
Xiao-Qin Luo, Yixin Kang, Shao-Bin Duan, et al.
Journal of Medical Internet Research (2023) Vol. 25, pp. e41142-e41142
Open Access | Times Cited: 24
Artificial intelligence-assisted selection and efficacy prediction of antineoplastic strategies for precision cancer therapy
Zhe Zhang, Xiawei Wei
Seminars in Cancer Biology (2023) Vol. 90, pp. 57-72
Closed Access | Times Cited: 24
Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design
Xinyi Wu, Huitian Lin, Renren Bai, et al.
European Journal of Medicinal Chemistry (2024) Vol. 268, pp. 116262-116262
Closed Access | Times Cited: 13
The role and future prospects of artificial intelligence algorithms in peptide drug development
Zhiheng Chen, Ruoxi Wang, Junqi Guo, et al.
Biomedicine & Pharmacotherapy (2024) Vol. 175, pp. 116709-116709
Open Access | Times Cited: 12
ACPPfel: Explainable deep ensemble learning for anticancer peptides prediction based on feature optimization
Mingyou Liu, Tao Wu, Xue Li, et al.
Frontiers in Genetics (2024) Vol. 15
Open Access | Times Cited: 11
mACPpred 2.0: Stacked Deep Learning for Anticancer Peptide Prediction with Integrated Spatial and Probabilistic Feature Representations
Vinoth Kumar Sangaraju, Nhat Truong Pham, Leyi Wei, et al.
Journal of Molecular Biology (2024) Vol. 436, Iss. 17, pp. 168687-168687
Closed Access | Times Cited: 10
Identification of cyclin protein using gradient boost decision tree algorithm
Hasan Zulfiqar, Shi-Shi Yuan, Qin-Lai Huang, et al.
Computational and Structural Biotechnology Journal (2021) Vol. 19, pp. 4123-4131
Open Access | Times Cited: 50
iThermo: A Sequence-Based Model for Identifying Thermophilic Proteins Using a Multi-Feature Fusion Strategy
Zahoor Ahmed, Hasan Zulfiqar, Abdullah Aman Khan, et al.
Frontiers in Microbiology (2022) Vol. 13
Open Access | Times Cited: 33
Development of Anticancer Peptides Using Artificial Intelligence and Combinational Therapy for Cancer Therapeutics
Ji Su Hwang, Seok Gi Kim, Tae Hwan Shin, et al.
Pharmaceutics (2022) Vol. 14, Iss. 5, pp. 997-997
Open Access | Times Cited: 32
Protein–DNA/RNA interactions: Machine intelligence tools and approaches in the era of artificial intelligence and big data
Feifei Cui, Zilong Zhang, Chen Cao, et al.
PROTEOMICS (2022) Vol. 22, Iss. 8
Closed Access | Times Cited: 30
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
Accelerating the Discovery of Anticancer Peptides through Deep Forest Architecture with Deep Graphical Representation
Lantian Yao, Wenshuo Li, Yuntian Zhang, et al.
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 5, pp. 4328-4328
Open Access | Times Cited: 18
TriNet: A tri-fusion neural network for the prediction of anticancer and antimicrobial peptides
Wanyun Zhou, Yufei Liu, Yingxin Li, et al.
Patterns (2023) Vol. 4, Iss. 3, pp. 100702-100702
Open Access | Times Cited: 18
ACP-ESM: A novel framework for classification of anticancer peptides using protein-oriented transformer approach
Zeynep Hilal Kilimci, Mustafa Yalçın
Artificial Intelligence in Medicine (2024) Vol. 156, pp. 102951-102951
Open Access | Times Cited: 7
MiRNA–disease association prediction based on meta-paths
Liang Yu, Yujia Zheng, Lin Gao
Briefings in Bioinformatics (2021) Vol. 23, Iss. 2
Closed Access | Times Cited: 33
PreTP-Stack: Prediction of Therapeutic Peptide Based on the Stacked Ensemble Learning
Ke Yan, Hongwu Lv, Jie Wen, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2022) Vol. 20, Iss. 2, pp. 1337-1344
Closed Access | Times Cited: 27
PreRBP-TL: prediction of species-specific RNA-binding proteins based on transfer learning
Jun Zhang, Ke Yan, Qingcai Chen, et al.
Bioinformatics (2022) Vol. 38, Iss. 8, pp. 2135-2143
Closed Access | Times Cited: 24
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