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:

Fu-SulfPred: Identification of Protein S-sulfenylation Sites by Fusing Forests via Chou’s General PseAAC
Lidong Wang, Ruijun Zhang, Yashuang Mu
Journal of Theoretical Biology (2018) Vol. 461, pp. 51-58
Closed Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

iEnhancer-5Step: Identifying enhancers using hidden information of DNA sequences via Chou's 5-step rule and word embedding
Nguyen Quoc Khanh Le, Edward Kien Yee Yapp, Quang‐Thai Ho, et al.
Analytical Biochemistry (2019) Vol. 571, pp. 53-61
Closed Access | Times Cited: 139
SPrenylC-PseAAC: A sequence-based model developed via Chou's 5-steps rule and general PseAAC for identifying S-prenylation sites in proteins
Waqar Hussain, Yaser Daanial Khan, Nouman Rasool, et al.
Journal of Theoretical Biology (2019) Vol. 468, pp. 1-11
Closed Access | Times Cited: 136
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
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
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
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
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
iMethylK-PseAAC: Improving Accuracy of Lysine Methylation Sites Identification by Incorporating Statistical Moments and Position Relative Features into General PseAAC via Chou’s 5-steps Rule
Sarah Ilyas, Waqar Hussain, Adeel Ashraf, et al.
Current Genomics (2019) Vol. 20, Iss. 4, pp. 275-292
Open Access | Times Cited: 64
iCrotoK-PseAAC: Identify lysine crotonylation sites by blending position relative statistical features according to the Chou’s 5-step rule
Sharaf J. Malebary, Muhammad Safi ur Rehman, Yaser Daanial Khan
PLoS ONE (2019) Vol. 14, Iss. 11, pp. e0223993-e0223993
Open Access | Times Cited: 62
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
iGluK-Deep: computational identification of lysine glutarylation sites using deep neural networks with general pseudo amino acid compositions
Sheraz Naseer, Rao Faizan Ali, Yaser Daanial Khan, et al.
Journal of Biomolecular Structure and Dynamics (2021) Vol. 40, Iss. 22, pp. 11691-11704
Closed Access | Times Cited: 51
pLoc_bal-mVirus: Predict Subcellular Localization of Multi-Label Virus Proteins by Chou's General PseAAC and IHTS Treatment to Balance Training Dataset
Xuan Xiao, Xiang Cheng, Gen-Qiang Chen, et al.
Medicinal Chemistry (2018) Vol. 15, Iss. 5, pp. 496-509
Closed Access | Times Cited: 58
Prediction of S-Sulfenylation Sites Using Statistical Moments Based Features via CHOU’S 5-Step Rule
Ahmad Hassan Butt, Yaser Daanial Khan
International Journal of Peptide Research and Therapeutics (2019) Vol. 26, Iss. 3, pp. 1291-1301
Closed Access | Times Cited: 53
Inspector: a lysine succinylation predictor based on edited nearest-neighbor undersampling and adaptive synthetic oversampling
Yan Zhu, Cangzhi Jia, Fuyi Li, et al.
Analytical Biochemistry (2020) Vol. 593, pp. 113592-113592
Closed Access | Times Cited: 49
Using CHOU'S 5-Steps Rule to Predict O-Linked Serine Glycosylation Sites by Blending Position Relative Features and Statistical Moment
Muhammad Aizaz Akmal, Waqar Hussain, Nouman Rasool, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2020) Vol. 18, Iss. 5, pp. 2045-2056
Closed Access | Times Cited: 44
SDBP-Pred: Prediction of single-stranded and double-stranded DNA-binding proteins by extending consensus sequence and K-segmentation strategies into PSSM
Farman Ali, Muhammad Arif, Zaheer Ullah Khan, et al.
Analytical Biochemistry (2019) Vol. 589, pp. 113494-113494
Closed Access | Times Cited: 43
A comprehensive review of the imbalance classification of protein post-translational modifications
Lijun Dou, Fenglong Yang, Lei Xu, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 5
Closed Access | Times Cited: 36
Impacts of Pseudo Amino Acid Components and 5-steps Rule to Proteomics and Proteome Analysis
Kuo‐Chen Chou
Current Topics in Medicinal Chemistry (2019) Vol. 19, Iss. 25, pp. 2283-2300
Closed Access | Times Cited: 39
Identifying FL11 subtype by characterizing tumor immune microenvironment in prostate adenocarcinoma via Chou's 5-steps rule
Lei Yang, Yingli Lv, Shiyuan Wang, et al.
Genomics (2019) Vol. 112, Iss. 2, pp. 1500-1515
Open Access | Times Cited: 35
SulSite-GTB: identification of protein S-sulfenylation sites by fusing multiple feature information and gradient tree boosting
Minghui Wang, Xiaoqiang Cui, Bin Yu, et al.
Neural Computing and Applications (2020) Vol. 32, Iss. 17, pp. 13843-13862
Closed Access | Times Cited: 33
Identifying Cancer Targets Based on Machine Learning Methods via Chou’s 5-steps Rule and General Pseudo Components
Ruirui Liang, Jiayang Xie, Chi Zhang, et al.
Current Topics in Medicinal Chemistry (2019) Vol. 19, Iss. 25, pp. 2301-2317
Closed Access | Times Cited: 33
Artificial Intelligence (AI) Tools Constructed via the 5-Steps Rule for Predicting Post-Translational Modifications
Chou Kuo‐Chen
Trends in Artificial Intelligence (2019) Vol. 3, Iss. 1
Open Access | Times Cited: 31
Proposing Pseudo Amino Acid Components is an Important Milestone for Proteome and Genome Analyses
Kuo‐Chen Chou
International Journal of Peptide Research and Therapeutics (2019) Vol. 26, Iss. 2, pp. 1085-1098
Closed Access | Times Cited: 29
Identifying N6-methyladenosine sites using extreme gradient boosting system optimized by particle swarm optimizer
Xiaowei Zhao, Ye Zhang, Ning Qiao, et al.
Journal of Theoretical Biology (2019) Vol. 467, pp. 39-47
Closed Access | Times Cited: 24
Page 1 - Next Page

Scroll to top