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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:

Using deformation energy to analyze nucleosome positioning in genomes
Wei Chen, Pengmian Feng, Hui Ding, et al.
Genomics (2015) Vol. 107, Iss. 2-3, pp. 69-75
Closed Access | Times Cited: 116

Showing 1-25 of 116 citing articles:

iACP: a sequence-based tool for identifying anticancer peptides
Wei Chen, Hui Ding, Pengmian Feng, et al.
Oncotarget (2016) Vol. 7, Iss. 13, pp. 16895-16909
Open Access | Times Cited: 409
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
iRNA-PseColl: Identifying the Occurrence Sites of Different RNA Modifications by Incorporating Collective Effects of Nucleotides into PseKNC
Pengmian Feng, Hui Ding, Hui Yang, et al.
Molecular Therapy — Nucleic Acids (2017) Vol. 7, pp. 155-163
Open Access | Times Cited: 285
iRNA-PseU: Identifying RNA pseudouridine sites.
Wei Chen, Hua Tang, Jing Ye, et al.
DOAJ (DOAJ: Directory of Open Access Journals) (2016) Vol. 5, pp. e332-e332
Closed Access | Times Cited: 284
Pse-in-One 2.0: An Improved Package of Web Servers for Generating Various Modes of Pseudo Components of DNA, RNA, and Protein Sequences
Bin Liu, Hao Wu, Kuo‐Chen Chou
Natural Science (2017) Vol. 09, Iss. 04, pp. 67-91
Open Access | Times Cited: 252
2L-piRNA: A Two-Layer Ensemble Classifier for Identifying Piwi-Interacting RNAs and Their Function
Bin Liu, Fan Yang, Kuo‐Chen Chou
Molecular Therapy — Nucleic Acids (2017) Vol. 7, pp. 267-277
Open Access | Times Cited: 241
iRNA-AI: identifying the adenosine to inosine editing sites in RNA sequences
Wei Chen, Pengmian Feng, Hui Yang, et al.
Oncotarget (2016) Vol. 8, Iss. 3, pp. 4208-4217
Open Access | Times Cited: 229
pLoc-mEuk: Predict subcellular localization of multi-label eukaryotic proteins by extracting the key GO information into general PseAAC
Xiang Cheng, Xuan Xiao, Kuo‐Chen Chou
Genomics (2017) Vol. 110, Iss. 1, pp. 50-58
Open Access | Times Cited: 228
iDHS-EL: identifying DNase I hypersensitive sites by fusing three different modes of pseudo nucleotide composition into an ensemble learning framework
Bin Liu, Long Ren, Kuo‐Chen Chou
Bioinformatics (2016) Vol. 32, Iss. 16, pp. 2411-2418
Closed Access | Times Cited: 208
iTerm-PseKNC: a sequence-based tool for predicting bacterial transcriptional terminators
Chao-Qin Feng, Zhao‐Yue Zhang, Xiaojuan Zhu, et al.
Bioinformatics (2018) Vol. 35, Iss. 9, pp. 1469-1477
Closed Access | Times Cited: 206
iRNAm5C-PseDNC: identifying RNA 5-methylcytosine sites by incorporating physical-chemical properties into pseudo dinucleotide composition
Wang‐Ren Qiu, Shiyu Jiang, Zhaochun Xu, et al.
Oncotarget (2017) Vol. 8, Iss. 25, pp. 41178-41188
Open Access | Times Cited: 198
pSumo-CD: predicting sumoylation sites in proteins with covariance discriminant algorithm by incorporating sequence-coupled effects into general PseAAC
Jianhua Jia, Liuxia Zhang, Zi Liu, et al.
Bioinformatics (2016) Vol. 32, Iss. 20, pp. 3133-3141
Open Access | Times Cited: 191
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
iOri-Human: identify human origin of replication by incorporating dinucleotide physicochemical properties into pseudo nucleotide composition
Chang-Jian Zhang, Hua Tang, Wenchao Li, et al.
Oncotarget (2016) Vol. 7, Iss. 43, pp. 69783-69793
Open Access | Times Cited: 175
iHyd-PseCp: Identify hydroxyproline and hydroxylysine in proteins by incorporating sequence-coupled effects into general PseAAC
Wang‐Ren Qiu, Bi‐Qian Sun, Xuan Xiao, et al.
Oncotarget (2016) Vol. 7, Iss. 28, pp. 44310-44321
Open Access | Times Cited: 161
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
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
iPhos‐PseEvo: Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into General PseAAC via Grey System Theory
Wang‐Ren Qiu, Bi‐Qian Sun, Xuan Xiao, et al.
Molecular Informatics (2016) Vol. 36, Iss. 5-6
Closed Access | Times Cited: 154
iPhos-PseEn: Identifying phosphorylation sites in proteins by fusing different pseudo components into an ensemble classifier
Wang‐Ren Qiu, Xuan Xiao, Zhaochun Xu, et al.
Oncotarget (2016) Vol. 7, Iss. 32, pp. 51270-51283
Open Access | Times Cited: 149
iATC-mHyb: a hybrid multi-label classifier for predicting the classification of anatomical therapeutic chemicals
Xiang Cheng, Shuguang Zhao, Xuan Xiao, et al.
Oncotarget (2017) Vol. 8, Iss. 35, pp. 58494-58503
Open Access | Times Cited: 136
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
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
SPalmitoylC-PseAAC: A sequence-based model developed via Chou's 5-steps rule and general PseAAC for identifying S-palmitoylation sites in proteins
Waqar Hussain, Yaser Daanial Khan, Nouman Rasool, et al.
Analytical Biochemistry (2018) Vol. 568, pp. 14-23
Closed Access | Times Cited: 122
Pse-Analysis: a python package for DNA/RNA and protein/peptide sequence analysis based on pseudo components and kernel methods
Bin Liu, Hao Wu, Deyuan Zhang, et al.
Oncotarget (2017) Vol. 8, Iss. 8, pp. 13338-13343
Open Access | Times Cited: 120
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
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