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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:

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

Showing 1-25 of 315 citing articles:

Predicting antimicrobial peptides with improved accuracy by incorporating the compositional, physico-chemical and structural features into Chou’s general PseAAC
Prabina Kumar Meher, Tanmaya Kumar Sahu, Varsha Saini, et al.
Scientific Reports (2017) Vol. 7, Iss. 1
Open Access | Times Cited: 453
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
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
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
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
MLACP: machine-learning-based prediction of anticancer peptides
Balachandran Manavalan, Shaherin Basith, Tae Hwan Shin, et al.
Oncotarget (2017) Vol. 8, Iss. 44, pp. 77121-77136
Open Access | Times Cited: 242
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
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
iATC-mISF: a multi-label classifier for predicting the classes of anatomical therapeutic chemicals
Xiang Cheng, Shuguang Zhao, Xuan Xiao, et al.
Bioinformatics (2016) Vol. 33, Iss. 3, pp. 341-346
Open Access | Times Cited: 217
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
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
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
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
pLoc-mAnimal: predict subcellular localization of animal proteins with both single and multiple sites
Xiang Cheng, Shuguang Zhao, Wei‐Zhong Lin, et al.
Bioinformatics (2017) Vol. 33, Iss. 22, pp. 3524-3531
Open Access | Times Cited: 183
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
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
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
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