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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:

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

Showing 1-25 of 68 citing articles:

A First Computational Frame for Recognizing Heparin-Binding Protein
Wen Zhu, Shi-Shi Yuan, Jian Li, et al.
Diagnostics (2023) Vol. 13, Iss. 14, pp. 2465-2465
Open Access | Times Cited: 66
pAtbP-EnC: Identifying Anti-Tubercular Peptides Using Multi-Feature Representation and Genetic Algorithm-Based Deep Ensemble Model
Shahid Akbar, Ali Raza, Tamara Al Shloul, et al.
IEEE Access (2023) Vol. 11, pp. 137099-137114
Open Access | Times Cited: 53
Immune cell infiltration-based signature for prognosis and immunogenomic analysis in breast cancer
Shiyuan Wang, Qi Zhang, Chunlu Yu, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 2, pp. 2020-2031
Closed Access | Times Cited: 130
Deep-AntiFP: Prediction of antifungal peptides using distanct multi-informative features incorporating with deep neural networks
Ashfaq Ahmad, Shahid Akbar, Salman Khan, et al.
Chemometrics and Intelligent Laboratory Systems (2020) Vol. 208, pp. 104214-104214
Closed Access | Times Cited: 85
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
pLoc_bal-mEuk: Predict Subcellular Localization of Eukaryotic Proteins by General PseAAC and Quasi-balancing Training Dataset
Kuo‐Chen Chou, Xiang Cheng, Xuan Xiao
Medicinal Chemistry (2018) Vol. 15, Iss. 5, pp. 472-485
Closed Access | Times Cited: 59
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
Application of Machine Learning for Drug–Target Interaction Prediction
Lei Xu, Xiaoqing Ru, Rong Song
Frontiers in Genetics (2021) Vol. 12
Open Access | Times Cited: 50
Identification of cyclin protein using gradient boost decision tree algorithm
Hasan Zulfiqar, Shi-Shi Yuan, Qin-Lai Huang, et al.
Computational and Structural Biotechnology Journal (2021) Vol. 19, pp. 4123-4131
Open Access | Times Cited: 50
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
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
Identification of Thermophilic Proteins Based on Sequence-Based Bidirectional Representations from Transformer-Embedding Features
Hongdi Pei, Jiayu Li, Shuhan Ma, et al.
Applied Sciences (2023) Vol. 13, Iss. 5, pp. 2858-2858
Open Access | Times Cited: 20
ATTIC is an integrated approach for predicting A-to-I RNA editing sites in three species
Ruyi Chen, Fuyi Li, Xudong Guo, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 3
Open Access | Times Cited: 17
RaacLogo: a new sequence logo generator by using reduced amino acid clusters
Lei Zheng, Dongyang Liu, Wuritu Yang, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Closed Access | Times Cited: 49
Identify DNA-Binding Proteins Through the Extreme Gradient Boosting Algorithm
Ziye Zhao, Wen Yang, Yixiao Zhai, et al.
Frontiers in Genetics (2022) Vol. 12
Open Access | Times Cited: 25
StackAHTPs: An explainable antihypertensive peptides identifier based on heterogeneous features and stacked learning approach
Ali Ghulam, Muhammad Arif, Ahsanullah Unar, et al.
IET Systems Biology (2025) Vol. 19, Iss. 1
Open Access
A Method for Prediction of Thermophilic Protein Based on Reduced Amino Acids and Mixed Features
Changli Feng, Zhaogui Ma, Deyun Yang, et al.
Frontiers in Bioengineering and Biotechnology (2020) Vol. 8
Open Access | Times Cited: 38
Machine Learning of Single-Cell Transcriptome Highly Identifies mRNA Signature by Comparing F-Score Selection with DGE Analysis
Pengfei Liang, Wuritu Yang, Xing Chen, et al.
Molecular Therapy — Nucleic Acids (2020) Vol. 20, pp. 155-163
Open Access | Times Cited: 37
RaacFold: a webserver for 3D visualization and analysis of protein structure by using reduced amino acid alphabets
Lei Zheng, Dongyang Liu, Yuan Alex Li, et al.
Nucleic Acids Research (2022) Vol. 50, Iss. W1, pp. W633-W638
Open Access | Times Cited: 19
Designing a structure-function alphabet of helix based on reduced amino acid clusters
Siqi Yang, Dongyang Liu, Yancheng Song, et al.
Archives of Biochemistry and Biophysics (2024) Vol. 754, pp. 109942-109942
Closed Access | Times Cited: 4
Exploration of the correlation between GPCRs and drugs based on a learning to rank algorithm
Xiaoqing Ru, Lida Wang, Lihong Li, et al.
Computers in Biology and Medicine (2020) Vol. 119, pp. 103660-103660
Closed Access | Times Cited: 30
Prediction of N7-methylguanosine sites in human RNA based on optimal sequence features
Yuhe R. Yang, Chi Ma, Jia-Shu Wang, et al.
Genomics (2020) Vol. 112, Iss. 6, pp. 4342-4347
Open Access | Times Cited: 27
Research progress of reduced amino acid alphabets in protein analysis and prediction
Yuchao Liang, Siqi Yang, Lei Zheng, et al.
Computational and Structural Biotechnology Journal (2022) Vol. 20, pp. 3503-3510
Open Access | Times Cited: 16
Empirical comparison and recent advances of computational prediction of hormone binding proteins using machine learning methods
Hasan Zulfiqar, Zhiling Guo, Bakanina Kissanga Grace-Mercure, et al.
Computational and Structural Biotechnology Journal (2023) Vol. 21, pp. 2253-2261
Open Access | Times Cited: 10
Amino Acid Reduction Can Help to Improve the Identification of Antimicrobial Peptides and Their Functional Activities
Gaifang Dong, Lei Zheng, Shenghui Huang, et al.
Frontiers in Genetics (2021) Vol. 12
Open Access | Times Cited: 20
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