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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:

Prediction of anti-inflammatory peptides by a sequence-based stacking ensemble model named AIPStack
Hua Deng, Chaofeng Lou, Zengrui Wu, et al.
iScience (2022) Vol. 25, Iss. 9, pp. 104967-104967
Open Access | Times Cited: 21

Showing 21 citing articles:

AIPs-SnTCN: Predicting Anti-Inflammatory Peptides Using fastText and Transformer Encoder-Based Hybrid Word Embedding with Self-Normalized Temporal Convolutional Networks
Ali Raza, Jamal Uddin, Abdullah Almuhaimeed, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 21, pp. 6537-6554
Closed Access | Times Cited: 74
AIPs-DeepEnC-GA: Predicting Anti-inflammatory Peptides using Embedded Evolutionary and Sequential Feature Integration with Genetic Algorithm based Deep Ensemble Model
Ali Raza, Jamal Uddin, Quan Zou, et al.
Chemometrics and Intelligent Laboratory Systems (2024), pp. 105239-105239
Closed Access | Times Cited: 19
Comprehensive Analysis of Computational Methods for Predicting Anti-inflammatory Peptides
Ali Raza, Jamal Uddin, Shahid Akbar, et al.
Archives of Computational Methods in Engineering (2024) Vol. 31, Iss. 6, pp. 3211-3229
Closed Access | Times Cited: 12
Therapeutic Peptide Development Revolutionized: Harnessing the Power of Artificial Intelligence for Drug Discovery
Samaneh Hashemi, Parisa Vosough, Saeed Taghizadeh, et al.
Heliyon (2024) Vol. 10, Iss. 22, pp. e40265-e40265
Open Access | Times Cited: 9
PepNet: an interpretable neural network for anti-inflammatory and antimicrobial peptides prediction using a pre-trained protein language model
Jiyun Han, Tongxin Kong, Juntao Liu
Communications Biology (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 8
Explainable machine learning-based fractional vegetation cover inversion and performance optimization – A case study of an alpine grassland on the Qinghai-Tibet Plateau
Xinhong Li, Jianjun Chen, Zizhen Chen, et al.
Ecological Informatics (2024) Vol. 82, pp. 102768-102768
Open Access | Times Cited: 7
DeepAIPs-Pred: Predicting Anti-Inflammatory Peptides Using Local Evolutionary Transformation Images and Structural Embedding-Based Optimal Descriptors with Self-Normalized BiTCNs
Shahid Akbar, Matee Ullah, Ali Raza, et al.
Journal of Chemical Information and Modeling (2024)
Closed Access | Times Cited: 5
Computational Methods for Predicting Chemical Reactivity of Covalent Compounds
Zhe Zhang, Ruyu Gao, Meiling Zhao, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access
Peptide classification landscape: An in-depth systematic literature review on peptide types, databases, datasets, predictors architectures and performance
Muhammad Nabeel Asim, Tayyaba Asif, Faiza Mehmood, et al.
Computers in Biology and Medicine (2025) Vol. 188, pp. 109821-109821
Closed Access
Chemical Characterization and Anti-Inflammatory Activity of Ailanthus altissima Flavonoids: Optimization of Extraction Process and Mechanistic Insights
Yu Liu, Yan Yong, Hongjuan Zhang, et al.
Natural Product Communications (2025) Vol. 20, Iss. 4
Open Access
AIPPT: Predicts anti-inflammatory peptides using the most characteristic subset of bases and sequences by stacking ensemble learning strategies
Ruiqi Liu, Xiuhao Fu, Shankai Yan, et al.
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2023), pp. 23-29
Closed Access | Times Cited: 7
Multi-Contrast MRI Reconstruction Based on Frequency Domain Separation and Cross-Self-Attention
Yiran Qiu, Haotian Zhang, Qiaoyu Ma, et al.
IEEE Access (2024) Vol. 12, pp. 55062-55076
Open Access | Times Cited: 2
A BERT-based approach for identifying anti-inflammatory peptides using sequence information
Teng Xu, Qian Wang, Zhigang Yang, et al.
Heliyon (2024) Vol. 10, Iss. 12, pp. e32951-e32951
Open Access | Times Cited: 2
Identification and Mechanism Elucidation of Anti-Inflammatory Peptides in Jinhua Ham: An Integrative In Silico and In Vitro Study
Xinran Dong, Yunhao Ma, Yong Xie, et al.
Journal of Agricultural and Food Chemistry (2023)
Closed Access | Times Cited: 4
TriStack enables accurate identification of antimicrobial and anti-inflammatory peptides by combining machine learning and deep learning approaches
Jiyun Han, Qixuan Chen, J. T. Su, et al.
Future Generation Computer Systems (2024) Vol. 161, pp. 259-268
Closed Access | Times Cited: 1
Machine Learning Tools for Peptide Bioactivity Evaluation – Implications for Cell Culture Media Optimization and the Broader Cultivated Meat Industry
Kathy Sharon Isaac, Michelle Combe, Greg Potter, et al.
Current Research in Food Science (2024) Vol. 9, pp. 100842-100842
Open Access | Times Cited: 1
DeepAIP: Deep learning for anti-inflammatory peptide prediction using pre-trained protein language model features based on contextual self-attention network
Lun Zhu, Qingguo Yang, Sen Yang
International Journal of Biological Macromolecules (2024) Vol. 280, pp. 136172-136172
Closed Access | Times Cited: 1
Prediction of IDO1 Inhibitors by a Fingerprint‐Based Stacking Ensemble Model Named IDO1Stack
Huimin Sun, Yang Qing, Xinxin Yu, et al.
ChemMedChem (2023) Vol. 18, Iss. 17
Closed Access | Times Cited: 2
PAMPred: A hierarchical evolutionary ensemble framework for identifying plant antimicrobial peptides
Zhaowei Wang, Jun Meng, Haibin Li, et al.
Computers in Biology and Medicine (2023) Vol. 166, pp. 107545-107545
Closed Access | Times Cited: 2
In Silico Prediction of ERRα Agonists Based on Combined Features and Stacking Ensemble Method
Jiahao Xu, Zejun Huang, Hao Duan, et al.
ChemMedChem (2024) Vol. 19, Iss. 20
Closed Access
The usability of stacking-based ensemble learning model in crime prediction: a systematic review
Canan Başar Eroğlu, Hüseyin Çakır
Crime Prevention and Community Safety (2024) Vol. 26, Iss. 4, pp. 440-489
Closed Access
Using the local symmetry in amino acids sequences of polypeptides to improve the predictive potential of models of their inhibitor activity
Alla P. Toropova, Andrey A. Toropov
Amino Acids (2023) Vol. 55, Iss. 10, pp. 1437-1445
Closed Access | Times Cited: 1
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