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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:

Machine learning for discovering missing or wrong protein function annotations
Felipe Kenji Nakano, Mathias Lietaert, Celine Vens
BMC Bioinformatics (2019) Vol. 20, Iss. 1
Open Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

UDSMProt: universal deep sequence models for protein classification
Nils Strodthoff, Patrick Wagner, Markus Wenzel, et al.
Bioinformatics (2020) Vol. 36, Iss. 8, pp. 2401-2409
Open Access | Times Cited: 155
Review on the Computational Genome Annotation of Sequences Obtained by Next-Generation Sequencing
Girum Fitihamlak Ejigu, Jaehee Jung
Biology (2020) Vol. 9, Iss. 9, pp. 295-295
Open Access | Times Cited: 88
Systems biology approaches integrated with artificial intelligence for optimized metabolic engineering
Mohamed Helmy, Derek J. Smith, Kumar Selvarajoo
Metabolic Engineering Communications (2020) Vol. 11, pp. e00149-e00149
Open Access | Times Cited: 81
PFmulDL: a novel strategy enabling multi-class and multi-label protein function annotation by integrating diverse deep learning methods
Weiqi Xia, Lingyan Zheng, Jiebin Fang, et al.
Computers in Biology and Medicine (2022) Vol. 145, pp. 105465-105465
Closed Access | Times Cited: 59
Active learning for hierarchical multi-label classification
Felipe Kenji Nakano, Ricardo Cerri, Celine Vens
Data Mining and Knowledge Discovery (2020) Vol. 34, Iss. 5, pp. 1496-1530
Open Access | Times Cited: 28
Deep tree-ensembles for multi-output prediction
Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
Pattern Recognition (2021) Vol. 121, pp. 108211-108211
Open Access | Times Cited: 23
Machine learning with requirements: A manifesto
Eleonora Giunchiglia, Fergus Imrie, Mihaela van der Schaar, et al.
Deleted Journal (2024), pp. 1-13
Open Access | Times Cited: 2
An informatic workflow for the enhanced annotation of excretory/secretory proteins of Haemonchus contortus
Yuanting Zheng, Neil D. Young, Jiangning Song, et al.
Computational and Structural Biotechnology Journal (2023) Vol. 21, pp. 2696-2704
Open Access | Times Cited: 6
Ensemble learning model for identifying the hallmark genes of NFκB/TNF signaling pathway in cancers
Yin-Yuan Su, Yuling Liu, Hsuan‐Cheng Huang, et al.
Journal of Translational Medicine (2023) Vol. 21, Iss. 1
Open Access | Times Cited: 5
Handling imbalance in hierarchical classification problems using local classifiers approaches
Rodolfo M. Pereira, Yandre M. G. Costa, Carlos N. Silla
Data Mining and Knowledge Discovery (2021) Vol. 35, Iss. 4, pp. 1564-1621
Closed Access | Times Cited: 11
Self-Paced Unified Representation Learning for Hierarchical Multi-Label Classification
Zixuan Yuan, Hao Liu, Haoyi Zhou, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 15, pp. 16623-16632
Open Access | Times Cited: 1
Genome Annotation and Analysis
Harsharan Singh, Mannatpreet Khaira, Karan Sharma, et al.
Elsevier eBooks (2024)
Closed Access | Times Cited: 1
Trends in biological data integration for the selection of enzymes and transcription factors related to cellulose and hemicellulose degradation in fungi
Jaire Alves Ferreira Filho, Rafaela Rossi Rosolen, Déborah Aires Almeida, et al.
3 Biotech (2021) Vol. 11, Iss. 11
Open Access | Times Cited: 6
Hierarchical multilabel classifier for gene ontology annotation using multihead and multiend deep CNN model
Xin Yuan, Erli Pang, Kui Lin, et al.
IEEJ Transactions on Electrical and Electronic Engineering (2020) Vol. 15, Iss. 7, pp. 1057-1064
Closed Access | Times Cited: 4
Predictive Bi-clustering Trees for Hierarchical Multi-label Classification
Bruna Zamith Santos, Felipe Kenji Nakano, Ricardo Cerri, et al.
Lecture notes in computer science (2021), pp. 701-718
Open Access | Times Cited: 4
Feature Selection for Hierarchical Multi-label Classification
Luan V. M. da Silva, Ricardo Cerri
Lecture notes in computer science (2021), pp. 196-208
Closed Access | Times Cited: 4
Leveraging class hierarchy for detecting missing annotations on hierarchical multi-label classification
Miguel Romero, Felipe Kenji Nakano, Jorge Finke, et al.
Computers in Biology and Medicine (2022) Vol. 152, pp. 106423-106423
Closed Access | Times Cited: 3
Deep forests with tree-embeddings and label imputation for weak-label learning
Pedro Ilídio, Ricardo Cerri, Celine Vens, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2024) Vol. 35, pp. 1-8
Closed Access
PROTA: A Robust Tool for Protamine Prediction Using a Hybrid Approach of Machine Learning and Deep Learning
Jorge G. Farías, Lisandra Herrera-Belén, Luis Felipe Herrera Jiménez, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 19, pp. 10267-10267
Open Access
Finding Significant Project Issues with Machine Learning
Narasimha Rao Vajjhala, Kenneth David Strang
Springer proceedings in mathematics & statistics (2023), pp. 13-22
Closed Access
Using Chou's Pseudo-Amino Acid Composition to Predict and Classify Oxygen Binding Proteins
Soumiya Hamena, Souham Meshoul, Salima Ouadfel
(2020) Vol. 18, pp. 67-70
Closed Access
Commentary: Novel but nascent
Dawn S. Hui, Richard Lee
Journal of Thoracic and Cardiovascular Surgery (2020) Vol. 162, Iss. 3, pp. 864-865
Open Access
Coherent Hierarchical Multi-Label Classification Networks
Eleonora Giunchiglia, Thomas Lukasiewicz
arXiv (Cornell University) (2020)
Closed Access
Deep tree-ensembles for multi-output prediction
Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
arXiv (Cornell University) (2020)
Closed Access
Multi-Label Classification Neural Networks with Hard Logical Constraints.
Eleonora Giunchiglia, Thomas Lukasiewicz
arXiv (Cornell University) (2021)
Closed Access
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