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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:

iNitro-Tyr: Prediction of Nitrotyrosine Sites in Proteins with General Pseudo Amino Acid Composition
Yan Xu, Xin Wen, Wen Lishu, et al.
PLoS ONE (2014) Vol. 9, Iss. 8, pp. e105018-e105018
Open Access | Times Cited: 232

Showing 1-25 of 232 citing articles:

Impacts of Bioinformatics to Medicinal Chemistry
Kuo‐Chen Chou
Medicinal Chemistry (2015) Vol. 11, Iss. 3, pp. 218-234
Closed Access | Times Cited: 527
iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition
Hao Lin, En-Ze Deng, Hui Ding, et al.
Nucleic Acids Research (2014) Vol. 42, Iss. 21, pp. 12961-12972
Open Access | Times Cited: 491
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
iEnhancer-2L: a two-layer predictor for identifying enhancers and their strength by pseudo k-tuple nucleotide composition
Bin Liu, Longyun Fang, Ren Long, et al.
Bioinformatics (2015) Vol. 32, Iss. 3, pp. 362-369
Open Access | Times Cited: 352
iRNA-Methyl: Identifying N6-methyladenosine sites using pseudo nucleotide composition
Wei Chen, Pengmian Feng, Hui Ding, et al.
Analytical Biochemistry (2015) Vol. 490, pp. 26-33
Closed Access | Times Cited: 336
iPromoter-2L: a two-layer predictor for identifying promoters and their types by multi-window-based PseKNC
Bin Liu, Fan Yang, De-Shuang Huang, et al.
Bioinformatics (2017) Vol. 34, Iss. 1, pp. 33-40
Open Access | Times Cited: 318
pSuc-Lys: Predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach
Jianhua Jia, Zi Liu, Xuan Xiao, et al.
Journal of Theoretical Biology (2016) Vol. 394, pp. 223-230
Closed Access | Times Cited: 315
iDNA-Prot|dis: Identifying DNA-Binding Proteins by Incorporating Amino Acid Distance-Pairs and Reduced Alphabet Profile into the General Pseudo Amino Acid Composition
Bin Liu, Jinghao Xu, Xun Lan, et al.
PLoS ONE (2014) Vol. 9, Iss. 9, pp. e106691-e106691
Open Access | Times Cited: 307
Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences
Wei Chen, Hao Lin, Kuo‐Chen Chou
Molecular BioSystems (2015) Vol. 11, Iss. 10, pp. 2620-2634
Closed Access | Times Cited: 305
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
iPPI-Esml: An ensemble classifier for identifying the interactions of proteins by incorporating their physicochemical properties and wavelet transforms into PseAAC
Jianhua Jia, Zi Liu, Xuan Xiao, et al.
Journal of Theoretical Biology (2015) Vol. 377, pp. 47-56
Closed Access | Times Cited: 277
iLoc-lncRNA: predict the subcellular location of lncRNAs by incorporating octamer composition into general PseKNC
Zhendong Su, Yan Huang, Zhao‐Yue Zhang, et al.
Bioinformatics (2018) Vol. 34, Iss. 24, pp. 4196-4204
Open Access | Times Cited: 273
iSuc-PseOpt: Identifying lysine succinylation sites in proteins by incorporating sequence-coupling effects into pseudo components and optimizing imbalanced training dataset
Jianhua Jia, Zi Liu, Xuan Xiao, et al.
Analytical Biochemistry (2015) Vol. 497, pp. 48-56
Closed Access | Times Cited: 266
Performance measures in evaluating machine learning based bioinformatics predictors for classifications
Ya-Sen Jiao, Pu-Feng Du
Quantitative Biology (2016) Vol. 4, Iss. 4, pp. 320-330
Open Access | Times Cited: 262
pRNAm-PC: Predicting N6-methyladenosine sites in RNA sequences via physical–chemical properties
Zi Liu, Xuan Xiao, Dong‐Jun Yu, et al.
Analytical Biochemistry (2015) Vol. 497, pp. 60-67
Closed Access | Times Cited: 257
iDNA-Methyl: Identifying DNA methylation sites via pseudo trinucleotide composition
Zi Liu, Xuan Xiao, Wang‐Ren Qiu, et al.
Analytical Biochemistry (2015) Vol. 474, pp. 69-77
Closed Access | Times Cited: 256
iPTM-mLys: identifying multiple lysine PTM sites and their different types
Wang‐Ren Qiu, Bi‐Qian Sun, Xuan Xiao, et al.
Bioinformatics (2016) Vol. 32, Iss. 20, pp. 3116-3123
Open Access | Times Cited: 254
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
iDrug-Target: predicting the interactions between drug compounds and target proteins in cellular networking via benchmark dataset optimization approach
Xuan Xiao, Jianliang Min, Wei‐Zhong Lin, et al.
Journal of Biomolecular Structure and Dynamics (2014) Vol. 33, Iss. 10, pp. 2221-2233
Open Access | Times Cited: 212
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
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
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