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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:

iKcr-PseEns: Identify lysine crotonylation sites in histone proteins with pseudo components and ensemble classifier
Wang‐Ren Qiu, Bi‐Qian Sun, Xuan Xiao, et al.
Genomics (2017) Vol. 110, Iss. 5, pp. 239-246
Closed Access | Times Cited: 160

Showing 1-25 of 160 citing articles:

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
iEnhancer-EL: identifying enhancers and their strength with ensemble learning approach
Bin Liu, Kai Li, De-Shuang Huang, et al.
Bioinformatics (2018) Vol. 34, Iss. 22, pp. 3835-3842
Open Access | Times Cited: 198
iRNA(m6A)-PseDNC: Identifying N6-methyladenosine sites using pseudo dinucleotide composition
Wei Chen, Hui Ding, Xu Zhou, et al.
Analytical Biochemistry (2018) Vol. 561-562, pp. 59-65
Closed Access | Times Cited: 187
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
Protein acetylation sites with complex-valued polynomial model
Wenzheng Bao, Bin Yang
Frontiers of Computer Science (2024) Vol. 18, Iss. 3
Closed Access | Times Cited: 26
Identification of protein subcellular localization via integrating evolutionary and physicochemical information into Chou’s general PseAAC
Yinan Shen, Jijun Tang, Fei Guo
Journal of Theoretical Biology (2018) Vol. 462, pp. 230-239
Closed Access | Times Cited: 153
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
iPhosT-PseAAC: Identify phosphothreonine sites by incorporating sequence statistical moments into PseAAC
Yaser Daanial Khan, Nouman Rasool, Waqar Hussain, et al.
Analytical Biochemistry (2018) Vol. 550, pp. 109-116
Closed Access | Times Cited: 128
MULTiPly: a novel multi-layer predictor for discovering general and specific types of promoters
Meng Zhang, Fuyi Li, Tatiana T. Marquez‐Lago, et al.
Bioinformatics (2019) Vol. 35, Iss. 17, pp. 2957-2965
Open Access | Times Cited: 120
Deep-Kcr: accurate detection of lysine crotonylation sites using deep learning method
Hao Lv, Fanny Dao, Zheng-Xing Guan, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 4
Closed Access | Times Cited: 114
iMem-2LSAAC: A two-level model for discrimination of membrane proteins and their types by extending the notion of SAAC into chou's pseudo amino acid composition
Muhammad Arif, Maqsood Hayat, Zahoor Jan
Journal of Theoretical Biology (2018) Vol. 442, pp. 11-21
Closed Access | Times Cited: 108
iPPI-PseAAC(CGR): Identify protein-protein interactions by incorporating chaos game representation into PseAAC
Jianhua Jia, Xiaoyan Li, Wang‐Ren Qiu, et al.
Journal of Theoretical Biology (2018) Vol. 460, pp. 195-203
Closed Access | Times Cited: 105
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
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
Prediction of citrullination sites by incorporating k-spaced amino acid pairs into Chou's general pseudo amino acid composition
Zhe Ju, Shiyun Wang
Gene (2018) Vol. 664, pp. 78-83
Closed Access | Times Cited: 96
iPhosH-PseAAC: Identify Phosphohistidine Sites in Proteins by Blending Statistical Moments and Position Relative Features According to the Chou's 5-Step Rule and General Pseudo Amino Acid Composition
Muhammad Awais, Waqar Hussain, Yaser Daanial Khan, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2019) Vol. 18, Iss. 2, pp. 596-610
Closed Access | Times Cited: 95
pLoc_bal-mHum: Predict subcellular localization of human proteins by PseAAC and quasi-balancing training dataset
Kuo‐Chen Chou, Xiang Cheng, Xuan Xiao
Genomics (2018) Vol. 111, Iss. 6, pp. 1274-1282
Open Access | Times Cited: 92
Advances in Predicting Subcellular Localization of Multi-label Proteins and its Implication for Developing Multi-target Drugs
Kuo‐Chen Chou
Current Medicinal Chemistry (2019) Vol. 26, Iss. 26, pp. 4918-4943
Closed Access | Times Cited: 91
Protein lysine crotonylation: past, present, perspective
Gaoyue Jiang, Chunxia Li, Meng Kai Lü, et al.
Cell Death and Disease (2021) Vol. 12, Iss. 7
Open Access | Times Cited: 91
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: 85
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
pLoc_bal-mGneg: Predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC
Xiang Cheng, Xuan Xiao, Kuo‐Chen Chou
Journal of Theoretical Biology (2018) Vol. 458, pp. 92-102
Closed 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
iN6-methylat (5-step): identifying DNA N6-methyladenine sites in rice genome using continuous bag of nucleobases via Chou’s 5-step rule
Nguyen Quoc Khanh Le
Molecular Genetics and Genomics (2019) Vol. 294, Iss. 5, pp. 1173-1182
Closed Access | Times Cited: 83
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
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