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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:

MethyRNA: a web server for identification of N6-methyladenosine sites
Wei Chen, Hua Tang, Hao Lin
Journal of Biomolecular Structure and Dynamics (2016) Vol. 35, Iss. 3, pp. 683-687
Closed Access | Times Cited: 122

Showing 1-25 of 122 citing articles:

Gene2vec: gene subsequence embedding for prediction of mammalian N6-methyladenosine sites from mRNA
Quan Zou, Pengwei Xing, Leyi Wei, et al.
RNA (2018) Vol. 25, Iss. 2, pp. 205-218
Open Access | Times Cited: 471
iDNA6mA-PseKNC: Identifying DNA N6-methyladenosine sites by incorporating nucleotide physicochemical properties into PseKNC
Pengmian Feng, Hui Yang, Hui Ding, et al.
Genomics (2018) Vol. 111, Iss. 1, pp. 96-102
Open Access | Times Cited: 298
iRNA-PseColl: Identifying the Occurrence Sites of Different RNA Modifications by Incorporating Collective Effects of Nucleotides into PseKNC
Pengmian Feng, Hui Ding, Hui Yang, et al.
Molecular Therapy — Nucleic Acids (2017) Vol. 7, pp. 155-163
Open Access | Times Cited: 285
Survey of Machine Learning Techniques in Drug Discovery
Natalie Stephenson, Emily Shane, Jessica Chase, et al.
Current Drug Metabolism (2018) Vol. 20, Iss. 3, pp. 185-193
Closed Access | Times Cited: 211
WHISTLE: a high-accuracy map of the human N6-methyladenosine (m6A) epitranscriptome predicted using a machine learning approach
Kunqi Chen, Zhen Wei, Qing Zhang, et al.
Nucleic Acids Research (2019) Vol. 47, Iss. 7, pp. e41-e41
Open Access | Times Cited: 199
PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine
Balachandran Manavalan, Tae Hwan Shin, Gwang Lee
Frontiers in Microbiology (2018) Vol. 9
Open Access | Times Cited: 182
iRNA-3typeA: Identifying Three Types of Modification at RNA’s Adenosine Sites
Wei Chen, Pengmian Feng, Hui Yang, et al.
Molecular Therapy — Nucleic Acids (2018) Vol. 11, pp. 468-474
Open Access | Times Cited: 181
M6APred-EL: A Sequence-Based Predictor for Identifying N6-methyladenosine Sites Using Ensemble Learning
Leyi Wei, Huangrong Chen, Ran Su
Molecular Therapy — Nucleic Acids (2018) Vol. 12, pp. 635-644
Open Access | Times Cited: 170
iRSpot-Pse6NC: Identifying recombination spots in Saccharomyces cerevisiae by incorporating hexamer composition into general PseKNC
Hui Yang, Wang‐Ren Qiu, Guoqing Liu, et al.
International Journal of Biological Sciences (2018) Vol. 14, Iss. 8, pp. 883-891
Open Access | Times Cited: 142
iMethyl-STTNC: Identification of N6-methyladenosine sites by extending the idea of SAAC into Chou's PseAAC to formulate RNA sequences
Shahid Akbar, Maqsood Hayat
Journal of Theoretical Biology (2018) Vol. 455, pp. 205-211
Closed Access | Times Cited: 140
iMRM: a platform for simultaneously identifying multiple kinds of RNA modifications
Kewei Liu, Wei Chen
Bioinformatics (2020) Vol. 36, Iss. 11, pp. 3336-3342
Open Access | Times Cited: 136
Detecting N6-methyladenosine sites from RNA transcriptomes using ensemble Support Vector Machines
Wei Chen, Pengwei Xing, Quan Zou
Scientific Reports (2017) Vol. 7, Iss. 1
Open Access | Times Cited: 122
Comprehensive review and assessment of computational methods for predicting RNA post-transcriptional modification sites from RNA sequences
Zhen Chen, Pei Zhao, Fuyi Li, et al.
Briefings in Bioinformatics (2019) Vol. 21, Iss. 5, pp. 1676-1696
Closed Access | Times Cited: 122
Comparing SVM and ANN based Machine Learning Methods for Species Identification of Food Contaminating Beetles
Halil Bişğin, Tanmay Bera, Hongjian Ding, et al.
Scientific Reports (2018) Vol. 8, Iss. 1
Open Access | Times Cited: 111
A Novel Hybrid Sequence-Based Model for Identifying Anticancer Peptides
Lei Xu, Guangmin Liang, Longjie Wang, et al.
Genes (2018) Vol. 9, Iss. 3, pp. 158-158
Open Access | Times Cited: 108
M6AMRFS: Robust Prediction of N6-Methyladenosine Sites With Sequence-Based Features in Multiple Species
Xiaoli Qiang, Huangrong Chen, Xiucai Ye, et al.
Frontiers in Genetics (2018) Vol. 9
Open Access | Times Cited: 106
m7GHub: deciphering the location, regulation and pathogenesis of internal mRNA N7-methylguanosine (m7G) sites in human
Bowen Song, Yujiao Tang, Kunqi Chen, et al.
Bioinformatics (2020) Vol. 36, Iss. 11, pp. 3528-3536
Open Access | Times Cited: 106
iN6-Methyl (5-step): Identifying RNA N6-methyladenosine sites using deep learning mode via Chou's 5-step rules and Chou's general PseKNC
Iman Nazari, Muhammad Tahir, Hilal Tayara, et al.
Chemometrics and Intelligent Laboratory Systems (2019) Vol. 193, pp. 103811-103811
Closed Access | Times Cited: 97
SeqSVM: A Sequence-Based Support Vector Machine Method for Identifying Antioxidant Proteins
Lei Xu, Guangmin Liang, Shuhua Shi, et al.
International Journal of Molecular Sciences (2018) Vol. 19, Iss. 6, pp. 1773-1773
Open Access | Times Cited: 91
Computational identification of N6-methyladenosine sites in multiple tissues of mammals
Fanny Dao, Hao Lv, Yuhe R. Yang, et al.
Computational and Structural Biotechnology Journal (2020) Vol. 18, pp. 1084-1091
Open Access | Times Cited: 84
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: 80
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
RNA methylation and diseases: experimental results, databases, Web servers and computational models
Xing Chen, Yazhou Sun, Hui Liu, et al.
Briefings in Bioinformatics (2017) Vol. 20, Iss. 3, pp. 896-917
Closed Access | Times Cited: 85
RFAthM6A: a new tool for predicting m6A sites in Arabidopsis thaliana
Xiaofeng Wang, Renxiang Yan
Plant Molecular Biology (2018) Vol. 96, Iss. 3, pp. 327-337
Closed Access | Times Cited: 67
Identifying N 6-methyladenosine sites in the Arabidopsis thaliana transcriptome
Wei Chen, Pengmian Feng, Hui Ding, et al.
Molecular Genetics and Genomics (2016) Vol. 291, Iss. 6, pp. 2225-2229
Closed Access | Times Cited: 63
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