Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Deep-AntiFP: Prediction of antifungal peptides using distanct multi-informative features incorporating with deep neural networks
Ashfaq Ahmad, Shahid Akbar, Salman Khan, et al.
Chemometrics and Intelligent Laboratory Systems (2020) Vol. 208, pp. 104214-104214
Closed Access | Times Cited: 85

Showing 1-25 of 85 citing articles:

cACP-DeepGram: Classification of anticancer peptides via deep neural network and skip-gram-based word embedding model
Shahid Akbar, Maqsood Hayat, Muhammad Tahir, et al.
Artificial Intelligence in Medicine (2022) Vol. 131, pp. 102349-102349
Closed Access | Times Cited: 98
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: 75
Recent Progress in the Discovery and Design of Antimicrobial Peptides Using Traditional Machine Learning and Deep Learning
Jielu Yan, Jianxiu Cai, Bob Zhang, et al.
Antibiotics (2022) Vol. 11, Iss. 10, pp. 1451-1451
Open Access | Times Cited: 71
iAFPs-Mv-BiTCN: Predicting antifungal peptides using self-attention transformer embedding and transform evolutionary based multi-view features with bidirectional temporal convolutional networks
Shahid Akbar, Quan Zou, Ali Raza, et al.
Artificial Intelligence in Medicine (2024) Vol. 151, pp. 102860-102860
Closed Access | Times Cited: 56
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: 54
Identification of novel inhibitors for SARS-CoV-2 as therapeutic options using machine learning-based virtual screening, molecular docking and MD simulation
Abdus Samad, Amar Ajmal, Arif Mahmood, et al.
Frontiers in Molecular Biosciences (2023) Vol. 10
Open Access | Times Cited: 52
ToxinPred 3.0: An improved method for predicting the toxicity of peptides
Anand Singh Rathore, Shubham Choudhury, Akanksha Arora, et al.
Computers in Biology and Medicine (2024) Vol. 179, pp. 108926-108926
Open Access | Times Cited: 45
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: 17
pACP-HybDeep: predicting anticancer peptides using binary tree growth based transformer and structural feature encoding with deep-hybrid learning
Muhammad Khalil Shahid, Maqsood Hayat, Wajdi Alghamdi, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 8
XGBoost-enhanced ensemble model using discriminative hybrid features for the prediction of sumoylation sites
Salman Khan, Sumaiya Noor, Tahir Javed, et al.
BioData Mining (2025) Vol. 18, Iss. 1
Open Access | Times Cited: 2
iAtbP-Hyb-EnC: Prediction of antitubercular peptides via heterogeneous feature representation and genetic algorithm based ensemble learning model
Shahid Akbar, Ashfaq Ahmad, Maqsood Hayat, et al.
Computers in Biology and Medicine (2021) Vol. 137, pp. 104778-104778
Closed Access | Times Cited: 76
AFP-CMBPred: Computational identification of antifreeze proteins by extending consensus sequences into multi-blocks evolutionary information
Farman Ali, Shahid Akbar, Ali Ghulam, et al.
Computers in Biology and Medicine (2021) Vol. 139, pp. 105006-105006
Closed Access | Times Cited: 71
iAFPs-EnC-GA: Identifying antifungal peptides using sequential and evolutionary descriptors based multi-information fusion and ensemble learning approach
Ashfaq Ahmad, Shahid Akbar, Muhammad Tahir, et al.
Chemometrics and Intelligent Laboratory Systems (2022) Vol. 222, pp. 104516-104516
Closed Access | Times Cited: 69
XGB-DrugPred: computational prediction of druggable proteins using eXtreme gradient boosting and optimized features set
Rahu Sikander, Ali Ghulam, Farman Ali
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 63
DBP-CNN: Deep learning-based prediction of DNA-binding proteins by coupling discrete cosine transform with two-dimensional convolutional neural network
Omar Barukab, Farman Ali, Wajdi Alghamdi, et al.
Expert Systems with Applications (2022) Vol. 197, pp. 116729-116729
Closed Access | Times Cited: 44
AFP-MFL: accurate identification of antifungal peptides using multi-view feature learning
Yitian Fang, Fan Xu, Lesong Wei, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 1
Closed Access | Times Cited: 36
Deep learning tools to accelerate antibiotic discovery
Angela Cesaro, Mojtaba Bagheri, Marcelo D. T. Torres, et al.
Expert Opinion on Drug Discovery (2023) Vol. 18, Iss. 11, pp. 1245-1257
Closed Access | Times Cited: 30
AFP-SPTS: An Accurate Prediction of Antifreeze Proteins Using Sequential and Pseudo-Tri-Slicing Evolutionary Features with an Extremely Randomized Tree
Adnan Khan, Jamal Uddin, Farman Ali, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 3, pp. 826-834
Closed Access | Times Cited: 29
Recent Advances in Machine Learning-Based Models for Prediction of Antiviral Peptides
Farman Ali, Harish Kumar, Wajdi Alghamdi, et al.
Archives of Computational Methods in Engineering (2023) Vol. 30, Iss. 7, pp. 4033-4044
Open Access | Times Cited: 26
Optimized Feature Learning for Anti-Inflammatory Peptide Prediction Using Parallel Distributed Computing
Salman Khan, Muhammad Abbas Khan, Mukhtaj Khan, et al.
Applied Sciences (2023) Vol. 13, Iss. 12, pp. 7059-7059
Open Access | Times Cited: 24
A hybrid residue based sequential encoding mechanism with XGBoost improved ensemble model for identifying 5-hydroxymethylcytosine modifications
Islam Uddin, Hamid Hussain Awan, Majdi Khalid, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 13
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
Deep-VEGF: deep stacked ensemble model for prediction of vascular endothelial growth factor by concatenating gated recurrent unit with two-dimensional convolutional neural network
Raed Alsini, Abdullah Almuhaimeed, Farman Ali, et al.
Journal of Biomolecular Structure and Dynamics (2024), pp. 1-11
Closed Access | Times Cited: 12
IP-GCN: A Deep Learning Model for Prediction of Insulin using Graph Convolutional Network for Diabetes Drug Design
Farman Ali, Majdi Khalid, Abdullah Almuhaimeed, et al.
Journal of Computational Science (2024) Vol. 81, pp. 102388-102388
Closed Access | Times Cited: 10
An ensemble computational model for prediction of clathrin protein by coupling machine learning with discrete cosine transform
Majdi Khalid, Farman Ali, Wajdi Alghamdi, et al.
Journal of Biomolecular Structure and Dynamics (2024), pp. 1-9
Closed Access | Times Cited: 9
Page 1 - Next Page

Scroll to top