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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:

i6mA-stack: A stacking ensemble-based computational prediction of DNA N6-methyladenine (6mA) sites in the Rosaceae genome
Jhabindra Khanal, Dae Young Lim, Hilal Tayara, et al.
Genomics (2020) Vol. 113, Iss. 1, pp. 582-592
Open Access | Times Cited: 38

Showing 1-25 of 38 citing articles:

An Explainable Supervised Machine Learning Model for Predicting Respiratory Toxicity of Chemicals Using Optimal Molecular Descriptors
Keerthana Jaganathan, Hilal Tayara, Kil To Chong
Pharmaceutics (2022) Vol. 14, Iss. 4, pp. 832-832
Open Access | Times Cited: 33
Deep6mAPred: A CNN and Bi-LSTM-based deep learning method for predicting DNA N6-methyladenosine sites across plant species
Xingyu Tang, Peijie Zheng, Xueyong Li, et al.
Methods (2022) Vol. 204, pp. 142-150
Closed Access | Times Cited: 30
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
Prediction of Drug-Induced Liver Toxicity Using SVM and Optimal Descriptor Sets
Keerthana Jaganathan, Hilal Tayara, Kil To Chong
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 15, pp. 8073-8073
Open Access | Times Cited: 33
DeepCap-Kcr: accurate identification and investigation of protein lysine crotonylation sites based on capsule network
Jhabindra Khanal, Hilal Tayara, Quan Zou, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Closed Access | Times Cited: 30
Identifying DNA N4-methylcytosine sites in the rosaceae genome with a deep learning model relying on distributed feature representation
Jhabindra Khanal, Hilal Tayara, Quan Zou, et al.
Computational and Structural Biotechnology Journal (2021) Vol. 19, pp. 1612-1619
Open Access | Times Cited: 29
DNA N6-Methyladenine Modification in Eukaryotic Genome
Hao Li, Ning Zhang, Yuechen Wang, et al.
Frontiers in Genetics (2022) Vol. 13
Open Access | Times Cited: 20
Identifying optimal variables for machine-learning-based fish distribution modeling
Shaohua Xu, Jintao Wang, Xinjun Chen, et al.
Canadian Journal of Fisheries and Aquatic Sciences (2024) Vol. 81, Iss. 6, pp. 687-698
Closed Access | Times Cited: 4
i6mA-Vote: Cross-Species Identification of DNA N6-Methyladenine Sites in Plant Genomes Based on Ensemble Learning With Voting
Zhixia Teng, Zhengnan Zhao, Yanjuan Li, et al.
Frontiers in Plant Science (2022) Vol. 13
Open Access | Times Cited: 17
Stack-DHUpred: Advancing the accuracy of dihydrouridine modification sites detection via stacking approach
Md. Harun-Or-Roshid, Kazuhiro Maeda, Le Thi Phan, et al.
Computers in Biology and Medicine (2023) Vol. 169, pp. 107848-107848
Closed Access | Times Cited: 10
N6-methyladenine identification using deep learning and discriminative feature integration
Salman Khan, Islam Uddin, Sumaiya Noor, et al.
BMC Medical Genomics (2025) Vol. 18, Iss. 1
Open Access
HD-6mAPred: a hybrid deep learning approach for accurate prediction of N6-methyladenine sites in plant species
Huimin Li, Wei Gao, Yi Tang, et al.
PeerJ (2025) Vol. 13, pp. e19463-e19463
Open Access
Prediction of RNA 5-Hydroxymethylcytosine Modifications Using Deep Learning
Syed Danish Ali, Jeehong Kim, Hilal Tayara, et al.
IEEE Access (2021) Vol. 9, pp. 8491-8496
Open Access | Times Cited: 23
BTFBS: Binding Prediction of Bacterial Transcription Factors and Binding Sites Based on Deep Learning
Bingbing Jin, Song Liang, Xiaoqian Liu, et al.
Mathematics (2025) Vol. 13, Iss. 4, pp. 589-589
Open Access
Epigenetic modification for horticultural plant improvement comes of age
Sadaruddin Chachar, Muzafaruddin Chachar, Adeel Riaz, et al.
Scientia Horticulturae (2021) Vol. 292, pp. 110633-110633
Closed Access | Times Cited: 20
I-DNAN6mA: Accurate Identification of DNA N6-Methyladenine Sites Using the Base-Pairing Map and Deep Learning
Xueqiang Fan, Bing Lin, Jun Hu, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 3, pp. 1076-1086
Closed Access | Times Cited: 7
CapsNh-Kcr: Capsule network-based prediction of lysine crotonylation sites in human non-histone proteins
Jhabindra Khanal, Jeevan Kandel, Hilal Tayara, et al.
Computational and Structural Biotechnology Journal (2022) Vol. 21, pp. 120-127
Open Access | Times Cited: 11
DL-SPhos: Prediction of serine phosphorylation sites using transformer language model
Palistha Shrestha, Jeevan Kandel, Hilal Tayara, et al.
Computers in Biology and Medicine (2024) Vol. 169, pp. 107925-107925
Closed Access | Times Cited: 2
SoftVoting6mA: An improved ensemble-based method for predicting DNA N6-methyladenine sites in cross-species genomes
Zhaoting Yin, Jianyi Lyu, Guiyang Zhang, et al.
Mathematical Biosciences & Engineering (2024) Vol. 21, Iss. 3, pp. 3798-3815
Open Access | Times Cited: 2
ncRDense: A novel computational approach for classification of non-coding RNA family by deep learning
Tuvshinbayar Chantsalnyam, Arslan Siraj, Hilal Tayara, et al.
Genomics (2021) Vol. 113, Iss. 5, pp. 3030-3038
Open Access | Times Cited: 14
Robust proportional overlapping analysis for feature selection in binary classification within functional genomic experiments
Muhammad Hamraz, Naz Gul, Mushtaq Raza, et al.
PeerJ Computer Science (2021) Vol. 7, pp. e562-e562
Open Access | Times Cited: 13
GC6mA-Pred: A deep learning approach to identify DNA N6-methyladenine sites in the rice genome
Jianhua Cai, Guobao Xiao, Ran Su
Methods (2022) Vol. 204, pp. 14-21
Closed Access | Times Cited: 7
PlantNh-Kcr: a deep learning model for predicting non-histone crotonylation sites in plants
Yanming Jiang, Renxiang Yan, Xiaofeng Wang
Plant Methods (2024) Vol. 20, Iss. 1
Open Access | Times Cited: 1
StackRAM: a cross-species method for identifying RNA N6-methyladenosine sites based on stacked ensemble
Yaqun Zhang, Zhaomin Yu, Bin Yu, et al.
Chemometrics and Intelligent Laboratory Systems (2022) Vol. 222, pp. 104495-104495
Open Access | Times Cited: 4
6mA-StackingCV: an improved stacking ensemble model for predicting DNA N6-methyladenine site
Guohua Huang, Xiaohong Huang, Wei Luo
BioData Mining (2023) Vol. 16, Iss. 1
Open Access | Times Cited: 2
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