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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:

Optimization of serine phosphorylation prediction in proteins by comparing human engineered features and deep representations
Sheraz Naseer, Waqar Hussain, Yaser Daanial Khan, et al.
Analytical Biochemistry (2020) Vol. 615, pp. 114069-114069
Closed Access | Times Cited: 58

Showing 1-25 of 58 citing articles:

Designing antimicrobial peptides using deep learning and molecular dynamic simulations
Qiushi Cao, Cheng Ge, Xuejie Wang, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 2
Closed Access | Times Cited: 55
Signal Peptide Efficiency: From High-Throughput Data to Prediction and Explanation
Stefano Grasso, Valentina Dabene, Margriet M. W. B. Hendriks, et al.
ACS Synthetic Biology (2023) Vol. 12, Iss. 2, pp. 390-404
Open Access | Times Cited: 29
iGluK-Deep: computational identification of lysine glutarylation sites using deep neural networks with general pseudo amino acid compositions
Sheraz Naseer, Rao Faizan Ali, Yaser Daanial Khan, et al.
Journal of Biomolecular Structure and Dynamics (2021) Vol. 40, Iss. 22, pp. 11691-11704
Closed Access | Times Cited: 51
The applications of deep learning algorithms on in silico druggable proteins identification
Lezheng Yu, Xue Li, Fengjuan Liu, et al.
Journal of Advanced Research (2022) Vol. 41, pp. 219-231
Open Access | Times Cited: 31
Predicting potential microbe–disease associations based on multi-source features and deep learning
Liugen Wang, Yan Wang, Chenxu Xuan, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 4
Closed Access | Times Cited: 18
A Review of Machine Learning and Algorithmic Methods for Protein Phosphorylation Site Prediction
Farzaneh Esmaili, Mahdi Pourmirzaei, Shahin Ramazi, et al.
Genomics Proteomics & Bioinformatics (2023) Vol. 21, Iss. 6, pp. 1266-1285
Open Access | Times Cited: 18
LBCEPred: a machine learning model to predict linear B-cell epitopes
Wajdi Alghamdi, Muhammad Attique, Ebraheem Alzahrani, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 3
Closed Access | Times Cited: 24
MPMABP: A CNN and Bi-LSTM-Based Method for Predicting Multi-Activities of Bioactive Peptides
You Li, Xueyong Li, Yuewu Liu, et al.
Pharmaceuticals (2022) Vol. 15, Iss. 6, pp. 707-707
Open Access | Times Cited: 24
MIND-S is a deep-learning prediction model for elucidating protein post-translational modifications in human diseases
Yu Yan, Jyun‐Yu Jiang, Mingzhou Fu, et al.
Cell Reports Methods (2023) Vol. 3, Iss. 3, pp. 100430-100430
Open Access | Times Cited: 13
iNitroY-Deep: Computational Identification of Nitrotyrosine Sites to Supplement Carcinogenesis Studies Using Deep Learning
Sheraz Naseer, Rao Faizan Ali, Suliman Mohamed Fati, et al.
IEEE Access (2021) Vol. 9, pp. 73624-73640
Open Access | Times Cited: 25
iAmideV-Deep: Valine Amidation Site Prediction in Proteins Using Deep Learning and Pseudo Amino Acid Compositions
Sheraz Naseer, Rao Faizan Ali, Amgad Muneer, et al.
Symmetry (2021) Vol. 13, Iss. 4, pp. 560-560
Open Access | Times Cited: 24
ORI-Deep: improving the accuracy for predicting origin of replication sites by using a blend of features and long short-term memory network
Mahwish Shahid, M. Ilyas, Waqar Hussain, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 2
Closed Access | Times Cited: 17
Handcrafted versus non-handcrafted (self-supervised) features for the classification of antimicrobial peptides: complementary or redundant?
César R. García‐Jacas, Luis A. García‐González, Félix Martínez-Rios, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 6
Closed Access | Times Cited: 15
Ensemble Learning for Hormone Binding Protein Prediction: A Promising Approach for Early Diagnosis of Thyroid Hormone Disorders in Serum
Ahmad Hassan Butt, Tamim Alkhalifah, Fahad Alturise, et al.
Diagnostics (2023) Vol. 13, Iss. 11, pp. 1940-1940
Open Access | Times Cited: 9
Hemolytic-Pred: A machine learning-based predictor for hemolytic proteins using position and composition-based features
Gulnaz Perveen, Fahad Alturise, Tamim Alkhalifah, et al.
Digital Health (2023) Vol. 9
Open Access | Times Cited: 9
DeepDBS: Identification of DNA-binding sites in protein sequences by using deep representations and random forest
Yaser Daanial Khan, Tamim Alkhalifah, Fahad Alturise, et al.
Methods (2024) Vol. 231, pp. 26-36
Closed Access | Times Cited: 3
IGPred‐HDnet: Prediction of Immunoglobulin Proteins Using Graphical Features and the Hierarchal Deep Learning‐Based Approach
Ali Zakir, Fahad Alturise, Tamim Alkhalifah, et al.
Computational Intelligence and Neuroscience (2023) Vol. 2023, Iss. 1
Open Access | Times Cited: 8
iDHU-Ensem: Identification of dihydrouridine sites through ensemble learning models
Muhammad Taseer Suleman, Fahad Alturise, Tamim Alkhalifah, et al.
Digital Health (2023) Vol. 9, pp. 205520762311659-205520762311659
Open Access | Times Cited: 8
BBB-PEP-prediction: improved computational model for identification of blood–brain barrier peptides using blending position relative composition specific features and ensemble modeling
Ansar Naseem, Fahad Alturise, Tamim Alkhalifah, et al.
Journal of Cheminformatics (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 8
Computational identification of 4-carboxyglutamate sites to supplement physiological studies using deep learning
Sheraz Naseer, Rao Faizan Ali, Suliman Mohamed Fati, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 12
Deep Learning Approaches for Detection of Breast Adenocarcinoma Causing Carcinogenic Mutations
Asghar Ali Shah, Fahad Alturise, Tamim Alkhalifah, et al.
International Journal of Molecular Sciences (2022) Vol. 23, Iss. 19, pp. 11539-11539
Open Access | Times Cited: 12
Pretoria: An effective computational approach for accurate and high-throughput identification of CD8+ t-cell epitopes of eukaryotic pathogens
Phasit Charoenkwan, Nalini Schaduangrat, Nhat Truong Pham, et al.
International Journal of Biological Macromolecules (2023) Vol. 238, pp. 124228-124228
Closed Access | Times Cited: 6
PseU-Pred: An ensemble model for accurate identification of pseudouridine sites
Muhammad Taseer Suleman, Yaser Daanial Khan
Analytical Biochemistry (2023) Vol. 676, pp. 115247-115247
Closed Access | Times Cited: 6
Identification of stress response proteins through fusion of machine learning models and statistical paradigms
Ebraheem Alzahrani, Wajdi Alghamdi, Malik Zaka Ullah, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 14
m1A-pred: Prediction of Modified 1-methyladenosine Sites in RNA Sequences through Artificial Intelligence
Muhammad Taseer Suleman, Yaser Daanial Khan
Combinatorial Chemistry & High Throughput Screening (2022) Vol. 25, Iss. 14, pp. 2473-2484
Closed Access | Times Cited: 9
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