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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:

A comprehensive comparison and analysis of computational predictors for RNA N6-methyladenosine sites of Saccharomyces cerevisiae
Xiaolei Zhu, Jingjing He, Shihao Zhao, et al.
Briefings in Functional Genomics (2019)
Closed Access | Times Cited: 60

Showing 1-25 of 60 citing articles:

sgRNACNN: identifying sgRNA on-target activity in four crops using ensembles of convolutional neural networks
Mengting Niu, Yuan Lin, Quan Zou
Plant Molecular Biology (2021) Vol. 105, Iss. 4-5, pp. 483-495
Closed Access | Times Cited: 103
Biological Sequence Classification: A Review on Data and General Methods
Chunyan Ao, Shihu Jiao, Yansu Wang, et al.
Research (2022) Vol. 2022
Open Access | Times Cited: 68
MRMD2.0: A Python Tool for Machine Learning with Feature Ranking and Reduction
Shida He, Fei Guo, Quan Zou, et al.
Current Bioinformatics (2020) Vol. 15, Iss. 10, pp. 1213-1221
Closed Access | Times Cited: 98
RF-PseU: A Random Forest Predictor for RNA Pseudouridine Sites
Zhibin Lv, Jun Zhang, Hui Ding, et al.
Frontiers in Bioengineering and Biotechnology (2020) Vol. 8
Open Access | Times Cited: 79
DeepM6ASeq-EL: prediction of human N6-methyladenosine (m6A) sites with LSTM and ensemble learning
Juntao Chen, Quan Zou, Jing Li
Frontiers of Computer Science (2021) Vol. 16, Iss. 2
Closed Access | Times Cited: 79
RMDisease: a database of genetic variants that affect RNA modifications, with implications for epitranscriptome pathogenesis
Kunqi Chen, Bowen Song, Yujiao Tang, et al.
Nucleic Acids Research (2020) Vol. 49, Iss. D1, pp. D1396-D1404
Open Access | Times Cited: 77
The role of m6A-related genes in the prognosis and immune microenvironment of pancreatic adenocarcinoma
Rong Tang, Yiyin Zhang, Chen Liang, et al.
PeerJ (2020) Vol. 8, pp. e9602-e9602
Open Access | Times Cited: 68
A Convolutional Neural Network Using Dinucleotide One-hot Encoder for identifying DNA N6-Methyladenine Sites in the Rice Genome
Zhibin Lv, Hui Ding, Lei Wang, et al.
Neurocomputing (2020) Vol. 422, pp. 214-221
Closed Access | Times Cited: 60
m6A-TSHub: Unveiling the Context-Specific m6A Methylation and m6A-Affecting Mutations in 23 Human Tissues
Bowen Song, Daiyun Huang, Yuxin Zhang, et al.
Genomics Proteomics & Bioinformatics (2022) Vol. 21, Iss. 4, pp. 678-694
Open Access | Times Cited: 29
6mA-RicePred: A Method for Identifying DNA N6-Methyladenine Sites in the Rice Genome Based on Feature Fusion
Qianfei Huang, Jun Zhang, Leyi Wei, et al.
Frontiers in Plant Science (2020) Vol. 11
Open Access | Times Cited: 45
Prediction of m5C Modifications in RNA Sequences by Combining Multiple Sequence Features
Lijun Dou, Xiaoling Li, Hui Ding, et al.
Molecular Therapy — Nucleic Acids (2020) Vol. 21, pp. 332-342
Open Access | Times Cited: 39
m6A-NeuralTool: Convolution Neural Tool for RNA N6-Methyladenosine Site Identification in Different Species
Mobeen Ur Rehman, Jeehong Kim, Hilal Tayara, et al.
IEEE Access (2021) Vol. 9, pp. 17779-17786
Open Access | Times Cited: 33
Geographic encoding of transcripts enabled high-accuracy and isoform-aware deep learning of RNA methylation
Daiyun Huang, Kunqi Chen, Bowen Song, et al.
Nucleic Acids Research (2022) Vol. 50, Iss. 18, pp. 10290-10310
Open Access | Times Cited: 23
Critical evaluation of web-based DNA N6-methyladenine site prediction tools
Md Mehedi Hasan, Watshara Shoombuatong, Hiroyuki Kurata, et al.
Briefings in Functional Genomics (2020) Vol. 20, Iss. 4, pp. 258-272
Closed Access | Times Cited: 37
LMI-DForest: A deep forest model towards the prediction of lncRNA-miRNA interactions
Wei Wang, Xiao‐Qing Guan, Muhammad Tahir Khan, et al.
Computational Biology and Chemistry (2020) Vol. 89, pp. 107406-107406
Closed Access | Times Cited: 36
T4SE-XGB: Interpretable Sequence-Based Prediction of Type IV Secreted Effectors Using eXtreme Gradient Boosting Algorithm
Tianhang Chen, Xiangeng Wang, Yanyi Chu, et al.
Frontiers in Microbiology (2020) Vol. 11
Open Access | Times Cited: 33
DNC4mC-Deep: Identification and Analysis of DNA N4-Methylcytosine Sites Based on Different Encoding Schemes By Using Deep Learning
Abdul Wahab, Omid Mahmoudi, Jeehong Kim, et al.
Cells (2020) Vol. 9, Iss. 8, pp. 1756-1756
Open Access | Times Cited: 32
PSBP-SVM: A Machine Learning-Based Computational Identifier for Predicting Polystyrene Binding Peptides
Chaolu Meng, Yang Hu, Ying Zhang, et al.
Frontiers in Bioengineering and Biotechnology (2020) Vol. 8
Open Access | Times Cited: 31
SubLocEP: a novel ensemble predictor of subcellular localization of eukaryotic mRNA based on machine learning
Jing Li, Lichao Zhang, He Shida, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 5
Closed Access | Times Cited: 30
iMethyl-Deep: N6 Methyladenosine Identification of Yeast Genome with Automatic Feature Extraction Technique by Using Deep Learning Algorithm
Omid Mahmoudi, Abdul Wahab, Kil To Chong
Genes (2020) Vol. 11, Iss. 5, pp. 529-529
Open Access | Times Cited: 27
m5CPred-SVM: a novel method for predicting m5C sites of RNA
Xiao Chen, Yi Xiong, Yinbo Liu, et al.
BMC Bioinformatics (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 27
HSM6AP: a high-precision predictor for the Homo sapiens N6-methyladenosine (m^6 A) based on multiple weights and feature stitching
Jing Li, He Shida, Fei Guo, et al.
RNA Biology (2021) Vol. 18, Iss. 11, pp. 1882-1892
Open Access | Times Cited: 25
Staem5: A novel computational approach for accurate prediction of m5C site
Di Chai, Cangzhi Jia, Jia Zheng, et al.
Molecular Therapy — Nucleic Acids (2021) Vol. 26, pp. 1027-1034
Open Access | Times Cited: 23
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
BERT-Kgly: A Bidirectional Encoder Representations From Transformers (BERT)-Based Model for Predicting Lysine Glycation Site for Homo sapiens
Yinbo Liu, Yufeng Liu, Gang-Ao Wang, et al.
Frontiers in Bioinformatics (2022) Vol. 2
Open Access | Times Cited: 15
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