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:

pLoc-mVirus: Predict subcellular localization of multi-location virus proteins via incorporating the optimal GO information into general PseAAC
Xiang Cheng, Xuan Xiao, Kuo‐Chen Chou
Gene (2017) Vol. 628, pp. 315-321
Closed Access | Times Cited: 159

Showing 26-50 of 159 citing articles:

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
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
iPSW(2L)-PseKNC: A two-layer predictor for identifying promoters and their strength by hybrid features via pseudo K-tuple nucleotide composition
Xuan Xiao, Zhaochun Xu, Wang‐Ren Qiu, et al.
Genomics (2018) Vol. 111, Iss. 6, pp. 1785-1793
Open Access | Times Cited: 88
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
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
Protein subcellular localization prediction tools
Maryam Gillani, Gianluca Pollastri
Computational and Structural Biotechnology Journal (2024) Vol. 23, pp. 1796-1807
Open Access | Times Cited: 12
Prediction of protein subcellular localization with oversampling approach and Chou's general PseAAC
Shengli Zhang, Xin Duan
Journal of Theoretical Biology (2017) Vol. 437, pp. 239-250
Closed Access | Times Cited: 87
Predicting protein submitochondrial locations by incorporating the pseudo-position specific scoring matrix into the general Chou's pseudo-amino acid composition
Wenying Qiu, Shan Li, Xiaoqiang Cui, et al.
Journal of Theoretical Biology (2018) Vol. 450, pp. 86-103
Closed Access | Times Cited: 78
Predicting subcellular localization of multi-label proteins by incorporating the sequence features into Chou's PseAAC
Faisal Javed, Maqsood Hayat
Genomics (2018) Vol. 111, Iss. 6, pp. 1325-1332
Closed Access | Times Cited: 77
pSSbond-PseAAC: Prediction of disulfide bonding sites by integration of PseAAC and statistical moments
Yaser Daanial Khan, Mehreen Jamil, Waqar Hussain, et al.
Journal of Theoretical Biology (2018) Vol. 463, pp. 47-55
Closed Access | Times Cited: 77
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: 76
Using Chou's general PseAAC to analyze the evolutionary relationship of receptor associated proteins (RAP) with various folding patterns of protein domains
S. Muthu Krishnan
Journal of Theoretical Biology (2018) Vol. 445, pp. 62-74
Closed Access | Times Cited: 72
Implications of Newly Identified Brain eQTL Genes and Their Interactors in Schizophrenia
Lei Cai, Tao Huang, Jingjing Su, et al.
Molecular Therapy — Nucleic Acids (2018) Vol. 12, pp. 433-442
Open Access | Times Cited: 72
iQSP: A Sequence-Based Tool for the Prediction and Analysis of Quorum Sensing Peptides Using Informative Physicochemical Properties
Phasit Charoenkwan, Nalini Schaduangrat, Chanin Nantasenamat, et al.
International Journal of Molecular Sciences (2019) Vol. 21, Iss. 1, pp. 75-75
Open Access | Times Cited: 71
Critical evaluation of web-based prediction tools for human protein subcellular localization
Yinan Shen, Yijie Ding, Jijun Tang, et al.
Briefings in Bioinformatics (2019) Vol. 21, Iss. 5, pp. 1628-1640
Closed Access | Times Cited: 70
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: 70
PPI‐Detect: A support vector machine model for sequence‐based prediction of protein–protein interactions
Sandra Romero‐Molina, Yasser B. Ruiz‐Blanco, Mirja Harms, et al.
Journal of Computational Chemistry (2019) Vol. 40, Iss. 11, pp. 1233-1242
Closed Access | Times Cited: 68
UbiSitePred: A novel method for improving the accuracy of ubiquitination sites prediction by using LASSO to select the optimal Chou's pseudo components
Xiaoqiang Cui, Zhaomin Yu, Bin Yu, et al.
Chemometrics and Intelligent Laboratory Systems (2018) Vol. 184, pp. 28-43
Open Access | Times Cited: 67
iRSpot-SPI: Deep learning-based recombination spots prediction by incorporating secondary sequence information coupled with physio-chemical properties via Chou's 5-step rule and pseudo components
Zaheer Ullah Khan, Farman Ali, Izhar Ahmed Khan, et al.
Chemometrics and Intelligent Laboratory Systems (2019) Vol. 189, pp. 169-180
Closed Access | Times Cited: 67
Accelerated search for perovskite materials with higher Curie temperature based on the machine learning methods
Xiuyun Zhai, Mingtong Chen, Wencong Lu
Computational Materials Science (2018) Vol. 151, pp. 41-48
Closed Access | Times Cited: 66
iNuc-ext-PseTNC: an efficient ensemble model for identification of nucleosome positioning by extending the concept of Chou’s PseAAC to pseudo-tri-nucleotide composition
Muhammad Tahir, Maqsood Hayat, Sher Afzal Khan
Molecular Genetics and Genomics (2018) Vol. 294, Iss. 1, pp. 199-210
Closed Access | Times Cited: 66
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: 65
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
SNARE-CNN: a 2D convolutional neural network architecture to identify SNARE proteins from high-throughput sequencing data
Nguyen Quoc Khanh Le, Van-Nui Nguyen
PeerJ Computer Science (2019) Vol. 5, pp. e177-e177
Open Access | Times Cited: 64
iRSpot-ADPM: Identify recombination spots by incorporating the associated dinucleotide product model into Chou’s pseudo components
Lichao Zhang, Liang Kong
Journal of Theoretical Biology (2018) Vol. 441, pp. 1-8
Closed Access | Times Cited: 62

Scroll to top