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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:

PIP-EL: A New Ensemble Learning Method for Improved Proinflammatory Peptide Predictions
Balachandran Manavalan, Tae Hwan Shin, Myeong Ok Kim, et al.
Frontiers in Immunology (2018) Vol. 9
Open Access | Times Cited: 111

Showing 1-25 of 111 citing articles:

Machine intelligence in peptide therapeutics: A next‐generation tool for rapid disease screening
Shaherin Basith, Balachandran Manavalan, Tae Hwan Shin, et al.
Medicinal Research Reviews (2020) Vol. 40, Iss. 4, pp. 1276-1314
Closed Access | Times Cited: 256
Meta-4mCpred: A Sequence-Based Meta-Predictor for Accurate DNA 4mC Site Prediction Using Effective Feature Representation
Balachandran Manavalan, Shaherin Basith, Tae Hwan Shin, et al.
Molecular Therapy — Nucleic Acids (2019) Vol. 16, pp. 733-744
Open Access | Times Cited: 200
mACPpred: A Support Vector Machine-Based Meta-Predictor for Identification of Anticancer Peptides
Vinothini Boopathi, Sathiyamoorthy Subramaniyam, Adeel Malik, et al.
International Journal of Molecular Sciences (2019) Vol. 20, Iss. 8, pp. 1964-1964
Open Access | Times Cited: 168
Accelerating antibiotic discovery through artificial intelligence
Marcelo C. R. Melo, Jacqueline R. M. A. Maasch, César de la Fuente‐Núñez
Communications Biology (2021) Vol. 4, Iss. 1
Open Access | Times Cited: 155
SDM6A: A Web-Based Integrative Machine-Learning Framework for Predicting 6mA Sites in the Rice Genome
Shaherin Basith, Balachandran Manavalan, Tae Hwan Shin, et al.
Molecular Therapy — Nucleic Acids (2019) Vol. 18, pp. 131-141
Open Access | Times Cited: 151
StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides
Phasit Charoenkwan, Wararat Chiangjong, Chanin Nantasenamat, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Closed Access | Times Cited: 112
Peptide-Based Vaccines for Tuberculosis
Wenping Gong, Chao Pan, Peng Cheng, et al.
Frontiers in Immunology (2022) Vol. 13
Open Access | Times Cited: 76
Machine learning for antimicrobial peptide identification and design
Fangping Wan, Felix Wong, James J. Collins, et al.
Nature Reviews Bioengineering (2024) Vol. 2, Iss. 5, pp. 392-407
Closed Access | Times Cited: 54
Anti-Cancer Peptides: Status and Future Prospects
Gehane Ghaly, Hatem Tallima, Eslam Dabbish, et al.
Molecules (2023) Vol. 28, Iss. 3, pp. 1148-1148
Open Access | Times Cited: 47
Computationally designed multi-epitope vaccine construct targeting the SARS-CoV-2 spike protein elicits robust immune responses in silico
Varughese Deepthi, Aswathy Sasikumar, Kochupurackal P. Mohanakumar, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 3
Identification of hormone binding proteins based on machine learning methods
Jiu-Xin Tan, Shi-Hao Li, Zimei Zhang, et al.
Mathematical Biosciences & Engineering (2019) Vol. 16, Iss. 4, pp. 2466-2480
Open Access | Times Cited: 135
CPPred-FL: a sequence-based predictor for large-scale identification of cell-penetrating peptides by feature representation learning
Xiaoli Qiang, Chen Zhou, Xiucai Ye, et al.
Briefings in Bioinformatics (2018)
Closed Access | Times Cited: 121
iUmami-SCM: A Novel Sequence-Based Predictor for Prediction and Analysis of Umami Peptides Using a Scoring Card Method with Propensity Scores of Dipeptides
Phasit Charoenkwan, Janchai Yana, Chanin Nantasenamat, et al.
Journal of Chemical Information and Modeling (2020) Vol. 60, Iss. 12, pp. 6666-6678
Closed Access | Times Cited: 121
Comparative analysis and prediction of quorum-sensing peptides using feature representation learning and machine learning algorithms
Leyi Wei, Jie Hu, Fuyi Li, et al.
Briefings in Bioinformatics (2018)
Closed Access | Times Cited: 115
iGHBP: Computational identification of growth hormone binding proteins from sequences using extremely randomised tree
Shaherin Basith, Balachandran Manavalan, Tae Hwan Shin, et al.
Computational and Structural Biotechnology Journal (2018) Vol. 16, pp. 412-420
Open Access | Times Cited: 111
Meta-iAVP: A Sequence-Based Meta-Predictor for Improving the Prediction of Antiviral Peptides Using Effective Feature Representation
Nalini Schaduangrat, Chanin Nantasenamat, Virapong Prachayasittikul, et al.
International Journal of Molecular Sciences (2019) Vol. 20, Iss. 22, pp. 5743-5743
Open Access | Times Cited: 111
Computer-aided prediction and design of IL-6 inducing peptides: IL-6 plays a crucial role in COVID-19
Anjali Dhall, Sumeet Patiyal, Neelam Sharma, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 2, pp. 936-945
Open Access | Times Cited: 110
iBitter-SCM: Identification and characterization of bitter peptides using a scoring card method with propensity scores of dipeptides
Phasit Charoenkwan, Janchai Yana, Nalini Schaduangrat, et al.
Genomics (2020) Vol. 112, Iss. 4, pp. 2813-2822
Closed Access | Times Cited: 104
PTPD: predicting therapeutic peptides by deep learning and word2vec
Chuanyan Wu, Rui Gao, Yusen Zhang, et al.
BMC Bioinformatics (2019) Vol. 20, Iss. 1
Open Access | Times Cited: 99
AtbPpred: A Robust Sequence-Based Prediction of Anti-Tubercular Peptides Using Extremely Randomized Trees
Balachandran Manavalan, Shaherin Basith, Tae Hwan Shin, et al.
Computational and Structural Biotechnology Journal (2019) Vol. 17, pp. 972-981
Open Access | Times Cited: 95
4mCpred-EL: An Ensemble Learning Framework for Identification of DNA N4-Methylcytosine Sites in the Mouse Genome
Balachandran Manavalan, Shaherin Basith, Tae Hwan Shin, et al.
Cells (2019) Vol. 8, Iss. 11, pp. 1332-1332
Open Access | Times Cited: 91
i4mC-ROSE, a bioinformatics tool for the identification of DNA N4-methylcytosine sites in the Rosaceae genome
Md Mehedi Hasan, Balachandran Manavalan, Mst. Shamima Khatun, et al.
International Journal of Biological Macromolecules (2019) Vol. 157, pp. 752-758
Closed Access | Times Cited: 82
iDPPIV-SCM: A Sequence-Based Predictor for Identifying and Analyzing Dipeptidyl Peptidase IV (DPP-IV) Inhibitory Peptides Using a Scoring Card Method
Phasit Charoenkwan, Sakawrat Kanthawong, Chanin Nantasenamat, et al.
Journal of Proteome Research (2020) Vol. 19, Iss. 10, pp. 4125-4136
Closed Access | Times Cited: 81
A survey on extraction of causal relations from natural language text
Jie Yang, Soyeon Caren Han, Josiah Poon
Knowledge and Information Systems (2022) Vol. 64, Iss. 5, pp. 1161-1186
Open Access | Times Cited: 65
Machine Learning Prediction of Antimicrobial Peptides
Guangshun Wang, Iosif I. Vaisman, Monique L. van Hoek
Methods in molecular biology (2022), pp. 1-37
Open Access | Times Cited: 61
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