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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:

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

Showing 1-25 of 208 citing articles:

Can machine-learning improve cardiovascular risk prediction using routine clinical data?
Stephen Weng, Jenna Reps, Joe Kai, et al.
PLoS ONE (2017) Vol. 12, Iss. 4, pp. e0174944-e0174944
Open Access | Times Cited: 1088
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
Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways
Lei Chen, Yu-Hang Zhang, ShaoPeng Wang, et al.
PLoS ONE (2017) Vol. 12, Iss. 9, pp. e0184129-e0184129
Open Access | Times Cited: 348
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
BioSeq-Analysis: a platform for DNA, RNA and protein sequence analysis based on machine learning approaches
Bin Liu
Briefings in Bioinformatics (2017) Vol. 20, Iss. 4, pp. 1280-1294
Closed Access | Times Cited: 301
iRSpot-EL: identify recombination spots with an ensemble learning approach
Bin Liu, Shanyi Wang, Long Ren, et al.
Bioinformatics (2016) Vol. 33, Iss. 1, pp. 35-41
Open Access | Times Cited: 295
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
Predicting diabetes mellitus using SMOTE and ensemble machine learning approach: The Henry Ford ExercIse Testing (FIT) project
Manal Alghamdi, Mouaz H. Al‐Mallah, Steven J. Keteyian, et al.
PLoS ONE (2017) Vol. 12, Iss. 7, pp. e0179805-e0179805
Open Access | Times Cited: 268
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
Development of machine learning models for diagnosis of glaucoma
Seong-Jae Kim, Kyong Jin Cho, Sejong Oh
PLoS ONE (2017) Vol. 12, Iss. 5, pp. e0177726-e0177726
Open Access | Times Cited: 241
Improved prediction of protein–protein interactions using novel negative samples, features, and an ensemble classifier
Leyi Wei, Pengwei Xing, Jiancang Zeng, et al.
Artificial Intelligence in Medicine (2017) Vol. 83, pp. 67-74
Closed Access | Times Cited: 232
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
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
Meta-4mCpred: A Sequence-Based Meta-Predictor for Accurate DNA 4mC Site Prediction Using Effective Feature Representation
Balachandran Manavalan, Shaherin Basith, Tae Hwan Shin, et al.
Molecular Therapy — Nucleic Acids (2019) Vol. 16, pp. 733-744
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
A novel hierarchical selective ensemble classifier with bioinformatics application
Leyi Wei, Shixiang Wan, Jiasheng Guo, et al.
Artificial Intelligence in Medicine (2017) Vol. 83, pp. 82-90
Closed Access | Times Cited: 194
CPPred-RF: A Sequence-based Predictor for Identifying Cell-Penetrating Peptides and Their Uptake Efficiency
Leyi Wei, Pengwei Xing, Ran Su, et al.
Journal of Proteome Research (2017) Vol. 16, Iss. 5, pp. 2044-2053
Closed Access | Times Cited: 193
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
BioSeq-BLM: a platform for analyzing DNA, RNA and protein sequences based on biological language models
Hongliang Li, Yihe Pang, Bin Liu
Nucleic Acids Research (2021) Vol. 49, Iss. 22, pp. e129-e129
Open Access | Times Cited: 171
A Survey on ensemble learning under the era of deep learning
Yongquan Yang, Haijun Lv, Ning Chen
Artificial Intelligence Review (2022) Vol. 56, Iss. 6, pp. 5545-5589
Closed Access | Times Cited: 162
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