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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 antioxidant proteins by incorporating statistical moments based features into Chou's PseAAC
Ahmad Hassan Butt, Nouman Rasool, Yaser Daanial Khan
Journal of Theoretical Biology (2019) Vol. 473, pp. 1-8
Closed Access | Times Cited: 60

Showing 1-25 of 60 citing articles:

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: 24
Progresses in Predicting Post-translational Modification
Kuo‐Chen Chou
International Journal of Peptide Research and Therapeutics (2019) Vol. 26, Iss. 2, pp. 873-888
Closed Access | Times Cited: 82
Evaluating machine learning methodologies for identification of cancer driver genes
Sharaf J. Malebary, Yaser Daanial Khan
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 66
Meta-iPVP: a sequence-based meta-predictor for improving the prediction of phage virion proteins using effective feature representation
Phasit Charoenkwan, Chanin Nantasenamat, Md Mehedi Hasan, et al.
Journal of Computer-Aided Molecular Design (2020) Vol. 34, Iss. 10, pp. 1105-1116
Closed Access | Times Cited: 68
Machine Learning Model for Identifying Antioxidant Proteins Using Features Calculated from Primary Sequences
Luu Ho Thanh Lam, Ngoc Le, Lê Văn Tuấn, et al.
Biology (2020) Vol. 9, Iss. 10, pp. 325-325
Open Access | Times Cited: 68
Prediction of antioxidant proteins using hybrid feature representation method and random forest
Chunyan Ao, Wenyang Zhou, Lin Gao, et al.
Genomics (2020) Vol. 112, Iss. 6, pp. 4666-4674
Closed Access | Times Cited: 63
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
CanLect-Pred: A Cancer Therapeutics Tool for Prediction of Target Cancerlectins Using Experiential Annotated Proteomic Sequences
Ahmad Hassan Butt, Yaser Daanial Khan
IEEE Access (2019) Vol. 8, pp. 9520-9531
Open Access | Times Cited: 56
iPhosS(Deep)-PseAAC: Identify Phosphoserine Sites in Proteins using Deep Learning on General Pseudo Amino Acid Compositions via Modified 5-Steps Rule
Sheraz Naseer, Waqar Hussain, Yaser Daanial Khan, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2020) Vol. 19, Iss. 3, pp. 1703-1714
Closed Access | Times Cited: 50
ProtoPred: Advancing Oncological Research Through Identification of Proto-Oncogene Proteins
Sharaf J. Malebary, Rabia Khan, Yaser Daanial Khan
IEEE Access (2021) Vol. 9, pp. 68788-68797
Open Access | Times Cited: 49
iSUMOK-PseAAC: prediction of lysine sumoylation sites using statistical moments and Chou’s PseAAC
Yaser Daanial Khan, Nabeel Sabir Khan, Sheraz Naseer, et al.
PeerJ (2021) Vol. 9, pp. e11581-e11581
Open Access | Times Cited: 46
Prediction of S-Sulfenylation Sites Using Statistical Moments Based Features via CHOU’S 5-Step Rule
Ahmad Hassan Butt, Yaser Daanial Khan
International Journal of Peptide Research and Therapeutics (2019) Vol. 26, Iss. 3, pp. 1291-1301
Closed Access | Times Cited: 53
Identification of Antimicrobial Peptides Using Chou’s 5 Step Rule
Sharaf J. Malebary, Yaser Daanial Khan
Computers, materials & continua/Computers, materials & continua (Print) (2021) Vol. 67, Iss. 3, pp. 2863-2881
Open Access | Times Cited: 35
Identification of antioxidant proteins using a discriminative intelligent model of k-space amino acid pairs based descriptors incorporating with ensemble feature selection
Ashfaq Ahmad, Shahid Akbar, Maqsood Hayat, et al.
Journal of Applied Biomedicine (2020) Vol. 42, Iss. 2, pp. 727-735
Closed Access | Times Cited: 35
Artificial Intelligence (AI) Tools Constructed via the 5-Steps Rule for Predicting Post-Translational Modifications
Chou Kuo‐Chen
Trends in Artificial Intelligence (2019) Vol. 3, Iss. 1
Open Access | Times Cited: 31
Application of artificial intelligence for detection of chemico-biological interactions associated with oxidative stress and DNA damage
Lazar M. Davidovic, Darko Laketić, Jelena Cumic, et al.
Chemico-Biological Interactions (2021) Vol. 345, pp. 109533-109533
Closed Access | Times Cited: 23
iAnt: Combination of Convolutional Neural Network and Random Forest Models Using PSSM and BERT Features to Identify Antioxidant Proteins
Hoang V. Tran, Quang H. Nguyen
Current Bioinformatics (2021) Vol. 17, Iss. 2, pp. 184-195
Closed Access | Times Cited: 23
4mC-RF: Improving the prediction of 4mC sites using composition and position relative features and statistical moment
Wajdi Alghamdi, Ebraheem Alzahrani, Malik Zaka Ullah, et al.
Analytical Biochemistry (2021) Vol. 633, pp. 114385-114385
Closed Access | Times Cited: 23
Transformation of heavy metals from contaminated water to soil, fodder and animals
Hina Kanwal, Ali Raza, Muhammad Saqlain Zaheer, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
Proposing Pseudo Amino Acid Components is an Important Milestone for Proteome and Genome Analyses
Kuo‐Chen Chou
International Journal of Peptide Research and Therapeutics (2019) Vol. 26, Iss. 2, pp. 1085-1098
Closed Access | Times Cited: 29
A machine learning technique for identifying DNA enhancer regions utilizing CIS-regulatory element patterns
Ahmad Hassan Butt, Tamim Alkhalifah, Fahad Alturise, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 12
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: 7
Prediction of Extracellular Matrix Proteins by Fusing Multiple Feature Information, Elastic Net, and Random Forest Algorithm
Minghui Wang, Lingling Yue, Xiaoqiang Cui, et al.
Mathematics (2020) Vol. 8, Iss. 2, pp. 169-169
Open Access | Times Cited: 16
Using Similarity Software to Evaluate Scientific Paper Quality Is a Big Mistake
Kuo‐Chen Chou
Natural Science (2020) Vol. 12, Iss. 03, pp. 42-58
Open Access | Times Cited: 15
Development of a machine learning-based predictor for identifying and discovering antioxidant peptides based on a new strategy
Yong Shen, Chunmei Liu, Kunmei Chi, et al.
Food Control (2021) Vol. 131, pp. 108439-108439
Closed Access | Times Cited: 13
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