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:

iPredCNC: Computational prediction model for cancerlectins and non-cancerlectins using novel cascade features subset selection
Zaheer Ullah Khan, Farman Ali, Irfan Ahmad, et al.
Chemometrics and Intelligent Laboratory Systems (2019) Vol. 195, pp. 103876-103876
Closed Access | Times Cited: 38

Showing 1-25 of 38 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: 94
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: 73
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: 68
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: 3
iHBP-DeepPSSM: Identifying hormone binding proteins using PsePSSM based evolutionary features and deep learning approach
Shahid Akbar, Salman Khan, Farman Ali, et al.
Chemometrics and Intelligent Laboratory Systems (2020) Vol. 204, pp. 104103-104103
Closed Access | Times Cited: 89
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
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: 60
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: 42
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: 26
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: 25
DEEP-EP: Identification of epigenetic protein by ensemble residual convolutional neural network for drug discovery
Farman Ali, Abdullah Almuhaimeed, Majdi Khalid, et al.
Methods (2024) Vol. 226, pp. 49-53
Closed Access | Times Cited: 11
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: 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: 8
Deep-AGP: Prediction of angiogenic protein by integrating two-dimensional convolutional neural network with discrete cosine transform
Farman Ali, Wajdi Alghamdi, Alaa Omran Almagrabi, et al.
International Journal of Biological Macromolecules (2023) Vol. 243, pp. 125296-125296
Closed Access | Times Cited: 16
Machine learning-based model for accurate identification of druggable proteins using light extreme gradient boosting
Omar Alghushairy, Farman Ali, Wajdi Alghamdi, et al.
Journal of Biomolecular Structure and Dynamics (2023) Vol. 42, Iss. 22, pp. 12330-12341
Closed Access | Times Cited: 16
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: 7
piEnPred: a bi-layered discriminative model for enhancers and their subtypes via novel cascade multi-level subset feature selection algorithm
Zaheer Ullah Khan, Dechang Pi, Shuanglong Yao, et al.
Frontiers of Computer Science (2021) Vol. 15, Iss. 6
Closed Access | Times Cited: 37
DBP-DeepCNN: Prediction of DNA-binding proteins using wavelet-based denoising and deep learning
Farman Ali, Harish Kumar, Shruti Patil, et al.
Chemometrics and Intelligent Laboratory Systems (2022) Vol. 229, pp. 104639-104639
Closed Access | Times Cited: 27
Target-DBPPred: An intelligent model for prediction of DNA-binding proteins using discrete wavelet transform based compression and light eXtreme gradient boosting
Farman Ali, Harish Kumar, Shruti Patil, et al.
Computers in Biology and Medicine (2022) Vol. 145, pp. 105533-105533
Closed Access | Times Cited: 26
DBP-iDWT: Improving DNA-Binding Proteins Prediction Using Multi-Perspective Evolutionary Profile and Discrete Wavelet Transform
Farman Ali, Omar Barukab, Ajay B. Gadicha, et al.
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-8
Open Access | Times Cited: 24
Prediction of antifreeze proteins using machine learning
Adnan Khan, Jamal Uddin, Farman Ali, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 23
Comparative analysis of the existing methods for prediction of antifreeze proteins
Adnan Khan, Jamal Uddin, Farman Ali, et al.
Chemometrics and Intelligent Laboratory Systems (2022) Vol. 232, pp. 104729-104729
Closed Access | Times Cited: 22
VEGF-ERCNN: A Deep Learning-based Model for Prediction of Vascular Endothelial Growth Factor using Ensemble Residual CNN
Farman Ali, Majdi Khalid, Atef Masmoudi, et al.
Journal of Computational Science (2024), pp. 102448-102448
Closed Access | Times Cited: 5
Comprehensive Analysis of Computational Models for Prediction of Anticancer Peptides Using Machine Learning and Deep Learning
Farman Ali, Norazlin Ibrahim, Raed Alsini, et al.
Archives of Computational Methods in Engineering (2025)
Closed Access
Leveraging deep learning for epigenetic protein prediction: a novel approach for early lung cancer diagnosis and drug discovery
Farman Ali, Abdullah Almuhaimeed, Wajdi Alghamdi, et al.
Health Information Science and Systems (2025) Vol. 13, Iss. 1
Closed Access
Page 1 - Next Page

Scroll to top