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:

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

Showing 1-25 of 295 citing articles:

Gene2vec: gene subsequence embedding for prediction of mammalian N6-methyladenosine sites from mRNA
Quan Zou, Pengwei Xing, Leyi Wei, et al.
RNA (2018) Vol. 25, Iss. 2, pp. 205-218
Open Access | Times Cited: 471

iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data
Zhen Chen, Pei Zhao, Fuyi Li, et al.
Briefings in Bioinformatics (2019) Vol. 21, Iss. 3, pp. 1047-1057
Closed Access | Times Cited: 372

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

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

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

Multi-categorical deep learning neural network to classify retinal images: A pilot study employing small database
Joon Yul Choi, Tae Keun Yoo, Jeong Gi Seo, et al.
PLoS ONE (2017) Vol. 12, Iss. 11, pp. e0187336-e0187336
Open Access | Times Cited: 251

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

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

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

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

Recurrent Neural Network for Predicting Transcription Factor Binding Sites
Zhen Shen, Wenzheng Bao, De-Shuang Huang
Scientific Reports (2018) Vol. 8, Iss. 1
Open Access | Times Cited: 198

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

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

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