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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 S-nitrosylation sites by integrating support vector machines and random forest
Md Mehedi Hasan, Balachandran Manavalan, Mst. Shamima Khatun, et al.
Molecular Omics (2019) Vol. 15, Iss. 6, pp. 451-458
Closed Access | Times Cited: 51

Showing 1-25 of 51 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: 254
HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation
Md Mehedi Hasan, Nalini Schaduangrat, Shaherin Basith, et al.
Bioinformatics (2020) Vol. 36, Iss. 11, pp. 3350-3356
Closed Access | Times Cited: 182
i6mA-Fuse: improved and robust prediction of DNA 6 mA sites in the Rosaceae genome by fusing multiple feature representation
Md Mehedi Hasan, Balachandran Manavalan, Watshara Shoombuatong, et al.
Plant Molecular Biology (2020) Vol. 103, Iss. 1-2, pp. 225-234
Closed Access | Times Cited: 77
NeuroPred-FRL: an interpretable prediction model for identifying neuropeptide using feature representation learning
Md Mehedi Hasan, Md. Ashad Alam, Watshara Shoombuatong, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Closed Access | Times Cited: 77
Prediction of bio-sequence modifications and the associations with diseases
Chunyan Ao, Liang Yu, Quan Zou
Briefings in Functional Genomics (2020) Vol. 20, Iss. 1, pp. 1-18
Closed Access | Times Cited: 72
STALLION: a stacking-based ensemble learning framework for prokaryotic lysine acetylation site prediction
Shaherin Basith, Gwang Lee, Balachandran Manavalan
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Open Access | Times Cited: 72
Research progress in the screening and evaluation of umami peptides
Lulu Qi, Xinchang Gao, Daodong Pan, et al.
Comprehensive Reviews in Food Science and Food Safety (2022) Vol. 21, Iss. 2, pp. 1462-1490
Closed Access | Times Cited: 59
Combining machine learning with structure-based protein design to predict and engineer post-translational modifications of proteins
Moritz Ertelt, Vikram Khipple Mulligan, Jack B. Maguire, et al.
PLoS Computational Biology (2024) Vol. 20, Iss. 3, pp. e1011939-e1011939
Open Access | Times Cited: 11
i4mC-Mouse: Improved identification of DNA N4-methylcytosine sites in the mouse genome using multiple encoding schemes
Md Mehedi Hasan, Balachandran Manavalan, Watshara Shoombuatong, et al.
Computational and Structural Biotechnology Journal (2020) Vol. 18, pp. 906-912
Open Access | Times Cited: 66
PVPred-SCM: Improved Prediction and Analysis of Phage Virion Proteins Using a Scoring Card Method
Phasit Charoenkwan, Sakawrat Kanthawong, Nalini Schaduangrat, et al.
Cells (2020) Vol. 9, Iss. 2, pp. 353-353
Open Access | Times Cited: 58
pLMSNOSite: an ensemble-based approach for predicting protein S-nitrosylation sites by integrating supervised word embedding and embedding from pre-trained protein language model
Pawel Pratyush, Suresh Pokharel, Hiroto Saigo, et al.
BMC Bioinformatics (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 16
Post-translational modification prediction via prompt-based fine-tuning of a GPT-2 model
Palistha Shrestha, Jeevan Kandel, Hilal Tayara, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 6
pCysMod: Prediction of Multiple Cysteine Modifications Based on Deep Learning Framework
Shihua Li, Kai Yu, Guandi Wu, et al.
Frontiers in Cell and Developmental Biology (2021) Vol. 9
Open Access | Times Cited: 40
iBitter-Fuse: A Novel Sequence-Based Bitter Peptide Predictor by Fusing Multi-View Features
Phasit Charoenkwan, Chanin Nantasenamat, Md Mehedi Hasan, et al.
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 16, pp. 8958-8958
Open Access | Times Cited: 38
Artificial intelligence approaches to the biochemistry of oxidative stress: Current state of the art
Igor Pantić, Jovana Paunović, Snežana Pejić, et al.
Chemico-Biological Interactions (2022) Vol. 358, pp. 109888-109888
Closed Access | Times Cited: 27
iAMY-SCM: Improved prediction and analysis of amyloid proteins using a scoring card method with propensity scores of dipeptides
Phasit Charoenkwan, Sakawrat Kanthawong, Chanin Nantasenamat, et al.
Genomics (2020) Vol. 113, Iss. 1, pp. 689-698
Open Access | Times Cited: 38
ProIn-Fuse: improved and robust prediction of proinflammatory peptides by fusing of multiple feature representations
Mst. Shamima Khatun, Md Mehedi Hasan, Watshara Shoombuatong, et al.
Journal of Computer-Aided Molecular Design (2020) Vol. 34, Iss. 12, pp. 1229-1236
Closed Access | Times Cited: 36
Evolution of Sequence-based Bioinformatics Tools for Protein-protein Interaction Prediction
Mst. Shamima Khatun, Watshara Shoombuatong, Md Mehedi Hasan, et al.
Current Genomics (2020) Vol. 21, Iss. 6, pp. 454-463
Open Access | Times Cited: 32
Oxidative Modification of Proteins: From Damage to Catalysis, Signaling, and Beyond
Marilene Demasi, Ohára Augusto, Etelvino José Henriques Bechara, et al.
Antioxidants and Redox Signaling (2021) Vol. 35, Iss. 12, pp. 1016-1080
Open Access | Times Cited: 31
Protein S-Nitrosylation: A Chemical Modification with Ubiquitous Biological Activities
Adam A. Aboalroub, Khaldun M. Al Azzam
The Protein Journal (2024) Vol. 43, Iss. 4, pp. 639-655
Closed Access | Times Cited: 4
In Silico Approaches for the Prediction and Analysis of Antiviral Peptides: A Review
Phasit Charoenkwan, Nuttapat Anuwongcharoen, Chanin Nantasenamat, et al.
Current Pharmaceutical Design (2020) Vol. 27, Iss. 18, pp. 2180-2188
Closed Access | Times Cited: 30
Computational prediction of protein ubiquitination sites mapping on Arabidopsis thaliana
Md. Parvez Mosharaf, Md. Mehedi Hassan, Fee Faysal Ahmed, et al.
Computational Biology and Chemistry (2020) Vol. 85, pp. 107238-107238
Closed Access | Times Cited: 28
Extremely-randomized-tree-based Prediction of N6-methyladenosine Sites inSaccharomyces cerevisiae
Rajiv Gandhi Govindaraj, Sathiyamoorthy Subramaniyam, Balachandran Manavalan
Current Genomics (2020) Vol. 21, Iss. 1, pp. 26-33
Open Access | Times Cited: 25
RecSNO: Prediction of Protein S-Nitrosylation Sites Using a Recurrent Neural Network
Arslan Siraj, Tuvshinbayar Chantsalnyam, Hilal Tayara, et al.
IEEE Access (2021) Vol. 9, pp. 6674-6682
Open Access | Times Cited: 20
iCysMod: an integrative database for protein cysteine modifications in eukaryotes
Panqin Wang, Qingfeng Zhang, Shihua Li, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 5
Closed Access | Times Cited: 23
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