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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.

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Showing 1-25 of 453 citing articles:

Deep learning improves antimicrobial peptide recognition
Daniel Veltri, Uday Kamath, Amarda Shehu
Bioinformatics (2018) Vol. 34, Iss. 16, pp. 2740-2747
Open Access | Times Cited: 425
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
Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations
Payel Das, Tom Sercu, Kahini Wadhawan, et al.
Nature Biomedical Engineering (2021) Vol. 5, Iss. 6, pp. 613-623
Open Access | Times Cited: 316
Identification of antimicrobial peptides from the human gut microbiome using deep learning
Yue Ma, Zhengyan Guo, Binbin Xia, et al.
Nature Biotechnology (2022) Vol. 40, Iss. 6, pp. 921-931
Closed Access | Times Cited: 314
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
AmPEP: Sequence-based prediction of antimicrobial peptides using distribution patterns of amino acid properties and random forest
Pratiti Bhadra, Jielu Yan, Jinyan Li, et al.
Scientific Reports (2018) Vol. 8, Iss. 1
Open Access | Times Cited: 255
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
LightGBM-PPI: Predicting protein-protein interactions through LightGBM with multi-information fusion
Cheng Chen, Qingmei Zhang, Qin Ma, et al.
Chemometrics and Intelligent Laboratory Systems (2019) Vol. 191, pp. 54-64
Open Access | Times Cited: 232
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
Antimicrobial Peptides: An Update on Classifications and Databases
Ahmer Bin Hafeez, Xukai Jiang, Phillip J. Bergen, et al.
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 21, pp. 11691-11691
Open Access | Times Cited: 224
Deep-AmPEP30: Improve Short Antimicrobial Peptides Prediction with Deep Learning
Jielu Yan, Pratiti Bhadra, Ang Li, et al.
Molecular Therapy — Nucleic Acids (2020) Vol. 20, pp. 882-894
Open Access | Times Cited: 219
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
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
Computer-Aided Design of Antimicrobial Peptides: Are We Generating Effective Drug Candidates?
Marlon H. Cardoso, Raquel Q. Orozco, Samilla B. Rezende, et al.
Frontiers in Microbiology (2020) Vol. 10
Open Access | Times Cited: 183
CAMPR4: a database of natural and synthetic antimicrobial peptides
Ulka Gawde, Shuvechha Chakraborty, Faiza Hanif Waghu, et al.
Nucleic Acids Research (2022) Vol. 51, Iss. D1, pp. D377-D383
Open Access | Times Cited: 141
AMPlify: attentive deep learning model for discovery of novel antimicrobial peptides effective against WHO priority pathogens
Chenkai Li, Darcy Sutherland, S. Austin Hammond, et al.
BMC Genomics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 126
Machine learning designs non-hemolytic antimicrobial peptides
Alice Capecchi, Xingguang Cai, Hippolyte Personne, et al.
Chemical Science (2021) Vol. 12, Iss. 26, pp. 9221-9232
Open Access | Times Cited: 115
Comprehensive assessment of machine learning-based methods for predicting antimicrobial peptides
Jing Xu, Fuyi Li, André Leier, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 5
Closed Access | Times Cited: 115
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