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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:

iRNA-PseKNC(2methyl): Identify RNA 2'-O-methylation sites by convolution neural network and Chou's pseudo components
Muhammad Tahir, Hilal Tayara, Kil To Chong
Journal of Theoretical Biology (2018) Vol. 465, pp. 1-6
Open Access | Times Cited: 101

Showing 1-25 of 101 citing articles:

DeePromoter: Robust Promoter Predictor Using Deep Learning
Mhaned Oubounyt, Zakaria Louadi, Hilal Tayara, et al.
Frontiers in Genetics (2019) Vol. 10
Open Access | Times Cited: 157
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
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
iDNA6mA (5-step rule): Identification of DNA N6-methyladenine sites in the rice genome by intelligent computational model via Chou's 5-step rule
Muhammad Tahir, Hilal Tayara, Kil To Chong
Chemometrics and Intelligent Laboratory Systems (2019) Vol. 189, pp. 96-101
Closed Access | Times Cited: 91
iHBP-DeepPSSM: Identifying hormone binding proteins using PsePSSM based evolutionary features and deep learning approach
Shahid Akbar, Salman Khan, Farman Ali, et al.
Chemometrics and Intelligent Laboratory Systems (2020) Vol. 204, pp. 104103-104103
Closed Access | Times Cited: 89
Prediction of lysine formylation sites using the composition of k-spaced amino acid pairs via Chou's 5-steps rule and general pseudo components
Zhe Ju, Shiyun Wang
Genomics (2019) Vol. 112, Iss. 1, pp. 859-866
Closed Access | Times Cited: 85
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
iPseU-CNN: Identifying RNA Pseudouridine Sites Using Convolutional Neural Networks
Muhammad Tahir, Hilal Tayara, Kil To Chong
Molecular Therapy — Nucleic Acids (2019) Vol. 16, pp. 463-470
Open Access | Times Cited: 84
MsDBP: Exploring DNA-Binding Proteins by Integrating Multiscale Sequence Information via Chou’s Five-Step Rule
Xiuquan Du, Yanyu Diao, Heng Liu, et al.
Journal of Proteome Research (2019) Vol. 18, Iss. 8, pp. 3119-3132
Closed Access | Times Cited: 84
Progresses in Predicting Post-translational Modification
Kuo‐Chen Chou
International Journal of Peptide Research and Therapeutics (2019) Vol. 26, Iss. 2, pp. 873-888
Closed Access | Times Cited: 82
H2Opred: a robust and efficient hybrid deep learning model for predicting 2’-O-methylation sites in human RNA
Nhat Truong Pham, Rajan Rakkiyapan, Jongsun Park, et al.
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 24
cACP: Classifying anticancer peptides using discriminative intelligent model via Chou’s 5-step rules and general pseudo components
Shahid Akbar, Ateeq Ur Rahman, Maqsood Hayat, et al.
Chemometrics and Intelligent Laboratory Systems (2019) Vol. 196, pp. 103912-103912
Closed Access | Times Cited: 75
RAACBook: a web server of reduced amino acid alphabet for sequence-dependent inference by using Chou’s five-step rule
Lei Zheng, Shenghui Huang, Nengjiang Mu, et al.
Database (2019) Vol. 2019
Open Access | Times Cited: 68
iSulfoTyr-PseAAC: Identify Tyrosine Sulfation Sites by Incorporating Statistical Moments via Chou’s 5-steps Rule and Pseudo Components
Omar Barukab, Yaser Daanial Khan, Sher Afzal Khan, et al.
Current Genomics (2019) Vol. 20, Iss. 4, pp. 306-320
Open Access | Times Cited: 65
4mCCNN: Identification of N4-Methylcytosine Sites in Prokaryotes Using Convolutional Neural Network
Jhabindra Khanal, Iman Nazari, Hilal Tayara, et al.
IEEE Access (2019) Vol. 7, pp. 145455-145461
Open Access | Times Cited: 63
Identifying Enhancers and Their Strength by the Integration of Word Embedding and Convolution Neural Network
Jhabindra Khanal, Hilal Tayara, Kil To Chong
IEEE Access (2020) Vol. 8, pp. 58369-58376
Open Access | Times Cited: 52
Identify RNA-associated subcellular localizations based on multi-label learning using Chou’s 5-steps rule
Hao Wang, Yijie Ding, Jijun Tang, et al.
BMC Genomics (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 45
NmRF: identification of multispecies RNA 2’-O-methylation modification sites from RNA sequences
Chunyan Ao, Quan Zou, Liang Yu
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Closed Access | Times Cited: 45
RFhy-m2G: Identification of RNA N2-methylguanosine modification sites based on random forest and hybrid features
Chunyan Ao, Quan Zou, Liang Yu
Methods (2021) Vol. 203, pp. 32-39
Closed Access | Times Cited: 43
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
Identification of prokaryotic promoters and their strength by integrating heterogeneous features
Hilal Tayara, Muhammad Tahir, Kil To Chong
Genomics (2019) Vol. 112, Iss. 2, pp. 1396-1403
Open Access | Times Cited: 52
Identifying DNase I hypersensitive sites using multi-features fusion and F-score features selection via Chou's 5-steps rule
Yunyun Liang, Shengli Zhang
Biophysical Chemistry (2019) Vol. 253, pp. 106227-106227
Closed Access | Times Cited: 49
Bioinformatics approaches for deciphering the epitranscriptome: Recent progress and emerging topics
Lian Liu, Bowen Song, Jiani Ma, et al.
Computational and Structural Biotechnology Journal (2020) Vol. 18, pp. 1587-1604
Open Access | Times Cited: 49
piEnPred: a bi-layered discriminative model for enhancers and their subtypes via novel cascade multi-level subset feature selection algorithm
Zaheer Ullah Khan, Dechang Pi, Shuanglong Yao, et al.
Frontiers of Computer Science (2021) Vol. 15, Iss. 6
Closed Access | Times Cited: 37
DNA sequences performs as natural language processing by exploiting deep learning algorithm for the identification of N4-methylcytosine
Abdul Wahab, Hilal Tayara, Zhenyu Xuan, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 36
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