Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

MGF6mARice: prediction of DNA N6-methyladenine sites in rice by exploiting molecular graph feature and residual block
Mengya Liu, Zhan-Li Sun, Zhigang Zeng, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 3
Closed Access | Times Cited: 12

Showing 12 citing articles:

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: 70
MuLan-Methyl—multiple transformer-based language models for accurate DNA methylation prediction
Wenhuan Zeng, Anupam Gautam, Daniel H. Huson
GigaScience (2022) Vol. 12
Open Access | Times Cited: 19
StructuralDPPIV: a novel deep learning model based on atom structure for predicting dipeptidyl peptidase-IV inhibitory peptides
Ding Wang, Junru Jin, Zhongshen Li, et al.
Bioinformatics (2024) Vol. 40, Iss. 2
Open Access | Times Cited: 2
MaskDNA-PGD: An innovative deep learning model for detecting DNA methylation by integrating mask sequences and adversarial PGD training as a data augmentation method
Zhiwei Zheng, Nguyen Quoc Khanh Le, Matthew Chin Heng Chua
Chemometrics and Intelligent Laboratory Systems (2022) Vol. 232, pp. 104715-104715
Closed Access | Times Cited: 11
MuLan-Methyl - Multiple Transformer-based Language Models for Accurate DNA Methylation Prediction
Wenhuan Zeng, Anupam Gautam, Daniel H. Huson
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 6
DeepPGD: A Deep Learning Model for DNA Methylation Prediction Using Temporal Convolution, BiLSTM, and Attention Mechanism
Shoryu Teragawa, Lei Wang, Yi Liu
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 15, pp. 8146-8146
Open Access | Times Cited: 1
GR-m6A: Prediction of N6-methyladenosine sites in mammals with molecular graph and residual network
Shi Qiu, Renxin Liu, Ying Liang
Computers in Biology and Medicine (2023) Vol. 163, pp. 107202-107202
Closed Access | Times Cited: 4
RiceSNP-BST: a deep learning framework for predicting biotic stress–associated SNPs in rice
Jiang Xu, Yujia Gao, Quan Lu, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 6
Open Access | Times Cited: 1
A review of methods for predicting DNA N6-methyladenine sites
Ke Han, Jianchun Wang, Yu Wang, et al.
Briefings in Bioinformatics (2022) Vol. 24, Iss. 1
Closed Access | Times Cited: 3
Predicting Drugs Suspected of Causing Adverse Drug Reactions Using Graph Features and Attention Mechanisms
Jinxiang Yang, Zuhai Hu, Liyuan Zhang, et al.
Pharmaceuticals (2024) Vol. 17, Iss. 7, pp. 822-822
Open Access
RiceSNP-ABST: a deep learning approach to identify abiotic stress-associated single nucleotide polymorphisms in rice
Quan Lu, Jiang Xu, Renyi Zhang, et al.
Briefings in Bioinformatics (2024) Vol. 26, Iss. 1
Open Access
PredinID: Predicting Pathogenic Inframe Indels in Human Through Graph Convolution Neural Network With Graph Sampling Technique
Zhenyu Yue, Ying Xiang, Guojun Chen, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2023) Vol. 20, Iss. 5, pp. 3226-3233
Closed Access | Times Cited: 1
StructuralDPPIV: A novel deep learning model based on atom-structure for predicting dipeptidyl peptidase-IV inhibitory peptides
Ding Wang, Junru Jin, Zhongshen Li, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 1
Page 1

Scroll to top