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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:

im6A-TS-CNN: Identifying the N6-Methyladenine Site in Multiple Tissues by Using the Convolutional Neural Network
Kewei Liu, Lei Cao, Pu-Feng Du, et al.
Molecular Therapy — Nucleic Acids (2020) Vol. 21, pp. 1044-1049
Open Access | Times Cited: 47

Showing 1-25 of 47 citing articles:

BERT4Bitter: a bidirectional encoder representations from transformers (BERT)-based model for improving the prediction of bitter peptides
Phasit Charoenkwan, Chanin Nantasenamat, Md Mehedi Hasan, et al.
Bioinformatics (2021) Vol. 37, Iss. 17, pp. 2556-2562
Closed Access | Times Cited: 134
Discovering Consensus Regions for Interpretable Identification of RNA N6-Methyladenosine Modification Sites via Graph Contrastive Clustering
Guodong Li, Bo-Wei Zhao, Xiaorui Su, et al.
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 28, Iss. 4, pp. 2362-2372
Closed Access | Times Cited: 23
Attention-based multi-label neural networks for integrated prediction and interpretation of twelve widely occurring RNA modifications
Zitao Song, Daiyun Huang, Bowen Song, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 85
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: 53
Critical downstream analysis steps for single-cell RNA sequencing data
Zilong Zhang, Feifei Cui, Chen Lin, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 5
Closed Access | Times Cited: 49
m5C-Related lncRNAs Predict Overall Survival of Patients and Regulate the Tumor Immune Microenvironment in Lung Adenocarcinoma
Junfan Pan, Zhidong Huang, Yiquan Xu
Frontiers in Cell and Developmental Biology (2021) Vol. 9
Open Access | Times Cited: 48
Towards a better prediction of subcellular location of long non-coding RNA
Zhao‐Yue Zhang, Zi‐Jie Sun, Yuhe Yang, et al.
Frontiers of Computer Science (2022) Vol. 16, Iss. 5
Closed Access | Times Cited: 35
DL-m6A: Identification of N6-Methyladenosine Sites in Mammals Using Deep Learning Based on Different Encoding Schemes
Mobeen Ur Rehman, Hilal Tayara, Kil To Chong
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2022) Vol. 20, Iss. 2, pp. 904-911
Closed Access | Times Cited: 30
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
TS-m6A-DL: Tissue-specific identification of N6-methyladenosine sites using a universal deep learning model
Zeeshan Abbas, Hilal Tayara, Quan Zou, et al.
Computational and Structural Biotechnology Journal (2021) Vol. 19, pp. 4619-4625
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
Deepm6A-MT: A deep learning-based method for identifying RNA N6-methyladenosine sites in multiple tissues
Guohua Huang, Xiaohong Huang, Jinyun Jiang
Methods (2024) Vol. 226, pp. 1-8
Closed Access | Times Cited: 4
Capturing short-range and long-range dependencies of nucleotides for identifying RNA N6-methyladenosine modification sites
Guodong Li, Bo-Wei Zhao, Xiaorui Su, et al.
Computers in Biology and Medicine (2025) Vol. 186, pp. 109625-109625
Closed Access
M6A-BERT-Stacking: A Tissue-Specific Predictor for Identifying RNA N6-Methyladenosine Sites Based on BERT and Stacking Strategy
Qianyue Li, Xin Cheng, Chen Song, et al.
Symmetry (2023) Vol. 15, Iss. 3, pp. 731-731
Open Access | Times Cited: 12
Comparative analysis of machine learning-based approaches for identifying therapeutic peptides targeting SARS-CoV-2
Balachandran Manavalan, Shaherin Basith, Gwang Lee
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Open Access | Times Cited: 23
Multi-task adaptive pooling enabled synergetic learning of RNA modification across tissue, type and species from low-resolution epitranscriptomes
Yiyou Song, Yue Wang, Xuan Wang, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 3
Closed Access | Times Cited: 10
BiLSTM- and CNN-Based m6A Modification Prediction Model for circRNAs
Yuqian Yuan, Xiaozhu Tang, Hongyan Li, et al.
Molecules (2024) Vol. 29, Iss. 11, pp. 2429-2429
Open Access | Times Cited: 3
Novel insight into the functions of N6‑methyladenosine modified lncRNAs in cancers (Review)
Ying‐Jie He, Xuezhi Du, Ming Chen, et al.
International Journal of Oncology (2022) Vol. 61, Iss. 6
Open Access | Times Cited: 15
N6-methyladenine RNA Methylation Epigenetic Modification and Kidney Diseases
Junjun Luan, Jeffrey B. Kopp, Hua Zhou
Kidney International Reports (2022) Vol. 8, Iss. 1, pp. 36-50
Open Access | Times Cited: 14
Enhancer-LSTMAtt: A Bi-LSTM and Attention-Based Deep Learning Method for Enhancer Recognition
Guohua Huang, Wei Luo, Guiyang Zhang, et al.
Biomolecules (2022) Vol. 12, Iss. 7, pp. 995-995
Open Access | Times Cited: 13
DeepLncPro: an interpretable convolutional neural network model for identifying long non-coding RNA promoters
Tianyang Zhang, Qiang Tang, Fulei Nie, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 6
Closed Access | Times Cited: 13
Interpretable prediction models for widespread m6A RNA modification across cell lines and tissues
Ying Zhang, Zhikang Wang, Yiwen Zhang, et al.
Bioinformatics (2023) Vol. 39, Iss. 12
Open Access | Times Cited: 7
m6AGE: A Predictor for N6-Methyladenosine Sites Identification Utilizing Sequence Characteristics and Graph Embedding-Based Geometrical Information
Yan Wang, Rui Guo, Lan Huang, et al.
Frontiers in Genetics (2021) Vol. 12
Open Access | Times Cited: 14
M6A-BiNP: predicting N6-methyladenosine sites based on bidirectional position-specific propensities of polynucleotides and pointwise joint mutual information
Mingzhao Wang, Juanying Xie, Sheng‐Quan Xu
RNA Biology (2021) Vol. 18, Iss. 12, pp. 2498-2512
Open Access | Times Cited: 13
m6A-TSHub: unveiling the context-specific m6A methylation and m6A-affecting mutations in 23 human tissues
Bowen Song, Daiyun Huang, Yuxin Zhang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 8
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