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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:

iSNO-AAPair: incorporating amino acid pairwise coupling into PseAAC for predicting cysteineS-nitrosylation sites in proteins
Yan Xu, Xiaojian Shao, Ling‐Yun Wu, et al.
PeerJ (2013) Vol. 1, pp. e171-e171
Open Access | Times Cited: 272

Showing 26-50 of 272 citing articles:

iSS-PseDNC: Identifying Splicing Sites Using Pseudo Dinucleotide Composition
Wei Chen, Pengmian Feng, Hao Lin, et al.
BioMed Research International (2014) Vol. 2014, pp. 1-12
Open Access | Times Cited: 205
iProt-Sub: a comprehensive package for accurately mapping and predicting protease-specific substrates and cleavage sites
Jiangning Song, Yanan Wang, Fuyi Li, et al.
Briefings in Bioinformatics (2018) Vol. 20, Iss. 2, pp. 638-658
Open Access | Times Cited: 204
iHyd-PseAAC: Predicting Hydroxyproline and Hydroxylysine in Proteins by Incorporating Dipeptide Position-Specific Propensity into Pseudo Amino Acid Composition
Yan Xu, Xin Wen, Xiaojian Shao, et al.
International Journal of Molecular Sciences (2014) Vol. 15, Iss. 5, pp. 7594-7610
Open Access | Times Cited: 200
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
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
iMethyl-PseAAC: Identification of Protein Methylation Sites via a Pseudo Amino Acid Composition Approach
Wang‐Ren Qiu, Xuan Xiao, Wei‐Zhong Lin, et al.
BioMed Research International (2014) Vol. 2014, pp. 1-12
Open Access | Times Cited: 188
pLoc-mPlant: predict subcellular localization of multi-location plant proteins by incorporating the optimal GO information into general PseAAC
Xiang Cheng, Xuan Xiao, Kuo‐Chen Chou
Molecular BioSystems (2017) Vol. 13, Iss. 9, pp. 1722-1727
Closed Access | Times Cited: 188
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
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
iCar-PseCp: identify carbonylation sites in proteins by Monte Carlo sampling and incorporating sequence coupled effects into general PseAAC
Jianhua Jia, Zi Liu, Xuan Xiao, et al.
Oncotarget (2016) Vol. 7, Iss. 23, pp. 34558-34570
Open Access | Times Cited: 174
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
PseDNA‐Pro: DNA‐Binding Protein Identification by Combining Chou’s PseAAC and Physicochemical Distance Transformation
Bin Liu, Jinghao Xu, Shixi Fan, et al.
Molecular Informatics (2014) Vol. 34, Iss. 1, pp. 8-17
Closed Access | Times Cited: 177
iUbiq-Lys: prediction of lysine ubiquitination sites in proteins by extracting sequence evolution information via a gray system model
Wang‐Ren Qiu, Xuan Xiao, Wei‐Zhong Lin, et al.
Journal of Biomolecular Structure and Dynamics (2014) Vol. 33, Iss. 8, pp. 1731-1742
Open Access | Times Cited: 165
pLoc-mGneg: Predict subcellular localization of Gram-negative bacterial proteins by deep gene ontology learning via general PseAAC
Xiang Cheng, Xuan Xiao, Kuo‐Chen Chou
Genomics (2017) Vol. 110, Iss. 4, pp. 231-239
Open Access | Times Cited: 165
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
iPPBS-Opt: A Sequence-Based Ensemble Classifier for Identifying Protein-Protein Binding Sites by Optimizing Imbalanced Training Datasets
Jianhua Jia, Zi Liu, Xuan Xiao, et al.
Molecules (2016) Vol. 21, Iss. 1, pp. 95-95
Open Access | Times Cited: 159
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
pLoc-mHum: predict subcellular localization of multi-location human proteins via general PseAAC to winnow out the crucial GO information
Xiang Cheng, Xuan Xiao, Kuo‐Chen Chou
Bioinformatics (2017) Vol. 34, Iss. 9, pp. 1448-1456
Open Access | Times Cited: 159
Quokka: a comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome
Fuyi Li, Chen Li, Tatiana T. Marquez‐Lago, et al.
Bioinformatics (2018) Vol. 34, Iss. 24, pp. 4223-4231
Open Access | Times Cited: 159
Identification of microRNA precursor with the degenerate K-tuple or Kmer strategy
Bin Liu, Longyun Fang, Shanyi Wang, et al.
Journal of Theoretical Biology (2015) Vol. 385, pp. 153-159
Closed Access | Times Cited: 156
iACP-GAEnsC: Evolutionary genetic algorithm based ensemble classification of anticancer peptides by utilizing hybrid feature space
Shahid Akbar, Maqsood Hayat, Muhammad Iqbal, et al.
Artificial Intelligence in Medicine (2017) Vol. 79, pp. 62-70
Closed Access | Times Cited: 152
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
DPP-PseAAC: A DNA-binding protein prediction model using Chou’s general PseAAC
Mohammad Saifur Rahman, Swakkhar Shatabda, Sanjay Saha, et al.
Journal of Theoretical Biology (2018) Vol. 452, pp. 22-34
Closed Access | Times Cited: 149
iMiRNA-PseDPC: microRNA precursor identification with a pseudo distance-pair composition approach
Bin Liu, Longyun Fang, Fule Liu, et al.
Journal of Biomolecular Structure and Dynamics (2015) Vol. 34, Iss. 1, pp. 223-235
Open Access | Times Cited: 146

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