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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:

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

Showing 26-50 of 200 citing articles:

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: 76
iBLP: An XGBoost-Based Predictor for Identifying Bioluminescent Proteins
Dan Zhang, Hua-Dong Chen, Hasan Zulfiqar, et al.
Computational and Mathematical Methods in Medicine (2021) Vol. 2021, pp. 1-15
Open Access | Times Cited: 75
Deep4mC: systematic assessment and computational prediction for DNA N4-methylcytosine sites by deep learning
Haodong Xu, Peilin Jia, Zhongming Zhao
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Open Access | Times Cited: 74
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
Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy
Md Mehedi Hasan, Sho Tsukiyama, Jae Youl Cho, et al.
Molecular Therapy (2022) Vol. 30, Iss. 8, pp. 2856-2867
Open Access | Times Cited: 66
Predicting protein–peptide binding residues via interpretable deep learning
Ruheng Wang, Junru Jin, Quan Zou, et al.
Bioinformatics (2022) Vol. 38, Iss. 13, pp. 3351-3360
Closed Access | Times Cited: 61
StackDPPIV: A novel computational approach for accurate prediction of dipeptidyl peptidase IV (DPP-IV) inhibitory peptides
Phasit Charoenkwan, Chanin Nantasenamat, Md Mehedi Hasan, et al.
Methods (2021) Vol. 204, pp. 189-198
Closed Access | Times Cited: 60
THRONE: A New Approach for Accurate Prediction of Human RNA N7-Methylguanosine Sites
Watshara Shoombuatong, Shaherin Basith, Thejkiran Pitti, et al.
Journal of Molecular Biology (2022) Vol. 434, Iss. 11, pp. 167549-167549
Closed Access | Times Cited: 50
BERT6mA: prediction of DNA N6-methyladenine site using deep learning-based approaches
Sho Tsukiyama, Md Mehedi Hasan, Hong‐Wen Deng, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 2
Open Access | Times Cited: 43
TACOS: a novel approach for accurate prediction of cell-specific long noncoding RNAs subcellular localization
Young-Jun Jeon, Md Mehedi Hasan, Hyun Woo Park, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 4
Open Access | Times Cited: 42
H2Opred: a robust and efficient hybrid deep learning model for predicting 2’-O-methylation sites in human RNA
Nhat Truong Pham, Rajan Rakkiyapan, Jongsun Park, et al.
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 26
iDNA-OpenPrompt: OpenPrompt learning model for identifying DNA methylation
Xia Yu, Jia Ren, Haixia Long, et al.
Frontiers in Genetics (2024) Vol. 15
Open Access | Times Cited: 14
iQSP: A Sequence-Based Tool for the Prediction and Analysis of Quorum Sensing Peptides Using Informative Physicochemical Properties
Phasit Charoenkwan, Nalini Schaduangrat, Chanin Nantasenamat, et al.
International Journal of Molecular Sciences (2019) Vol. 21, Iss. 1, pp. 75-75
Open Access | Times Cited: 71
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: 69
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
A hybrid Grey Wolf Optimization and Particle Swarm Optimization with C4.5 approach for prediction of Rheumatoid Arthritis
Shanmugam Sundaramurthy, Preethi Jayavel
Applied Soft Computing (2020) Vol. 94, pp. 106500-106500
Closed Access | Times Cited: 58
A Method for Identifying Vesicle Transport Proteins Based on LibSVM and MRMD
Zhiyu Tao, Yanjuan Li, Zhixia Teng, et al.
Computational and Mathematical Methods in Medicine (2020) Vol. 2020, pp. 1-9
Open Access | Times Cited: 57
Pred-BVP-Unb: Fast prediction of bacteriophage Virion proteins using un-biased multi-perspective properties with recursive feature elimination
Muhammad Arif, Farman Ali, Saeed Ahmad, et al.
Genomics (2019) Vol. 112, Iss. 2, pp. 1565-1574
Open Access | Times Cited: 55
Integrative machine learning framework for the identification of cell-specific enhancers from the human genome
Shaherin Basith, Md Mehedi Hasan, Gwang Lee, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Closed Access | Times Cited: 55
iTTCA-Hybrid: Improved and robust identification of tumor T cell antigens by utilizing hybrid feature representation
Phasit Charoenkwan, Chanin Nantasenamat, Md Mehedi Hasan, et al.
Analytical Biochemistry (2020) Vol. 599, pp. 113747-113747
Closed Access | Times Cited: 54
Deep-4mCW2V: A sequence-based predictor to identify N4-methylcytosine sites in Escherichia coli
Hasan Zulfiqar, Zi‐Jie Sun, Qin-Lai Huang, et al.
Methods (2021) Vol. 203, pp. 558-563
Closed Access | Times Cited: 54
Escherichia Coli DNA N-4-Methycytosine Site Prediction Accuracy Improved by Light Gradient Boosting Machine Feature Selection Technology
Zhibin Lv, Donghua Wang, Hui Ding, et al.
IEEE Access (2020) Vol. 8, pp. 14851-14859
Open Access | Times Cited: 53
Identification of cyclin protein using gradient boost decision tree algorithm
Hasan Zulfiqar, Shi-Shi Yuan, Qin-Lai Huang, et al.
Computational and Structural Biotechnology Journal (2021) Vol. 19, pp. 4123-4131
Open Access | Times Cited: 51
C-Loss Based Higher Order Fuzzy Inference Systems for Identifying DNA N4-Methylcytosine Sites
Yijie Ding, Prayag Tiwari, Quan Zou, et al.
IEEE Transactions on Fuzzy Systems (2022) Vol. 30, Iss. 11, pp. 4754-4765
Open Access | Times Cited: 37

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