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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:

Metabolic networks classification and knowledge discovery by information granulation
Alessio Martino, Alessandro Giuliani, Virginia Todde, et al.
Computational Biology and Chemistry (2019) Vol. 84, pp. 107187-107187
Closed Access | Times Cited: 21

Showing 21 citing articles:

Role of Inositols and Inositol Phosphates in Energy Metabolism
Saimai Chatree, Nanthaphop Thongmaen, Kwanchanit Tantivejkul, et al.
Molecules (2020) Vol. 25, Iss. 21, pp. 5079-5079
Open Access | Times Cited: 115
Myo-Inositol and D-Chiro-Inositol as Modulators of Ovary Steroidogenesis: A Narrative Review
Mariano Bizzarri, Noemi Monti, Aurora Piombarolo, et al.
Nutrients (2023) Vol. 15, Iss. 8, pp. 1875-1875
Open Access | Times Cited: 17
Exploiting Cliques for Granular Computing-based Graph Classification
Luca Baldini, Alessio Martino, Antonello Rizzi
2022 International Joint Conference on Neural Networks (IJCNN) (2020), pp. 1-9
Open Access | Times Cited: 11
(Hyper)graph Kernels over Simplicial Complexes
Alessio Martino, Antonello Rizzi
Entropy (2020) Vol. 22, Iss. 10, pp. 1155-1155
Open Access | Times Cited: 11
An Ecology-based Index for Text Embedding and Classification
Alessio Martino, Enrico De Santis, Antonello Rizzi
2022 International Joint Conference on Neural Networks (IJCNN) (2020), pp. 1-8
Open Access | Times Cited: 9
Towards a Class-Aware Information Granulation for Graph Embedding and Classification
Luca Baldini, Alessio Martino, Antonello Rizzi
Studies in computational intelligence (2021), pp. 263-290
Closed Access | Times Cited: 9
Deep learning neural network derivation and testing to distinguish acute poisonings
Omid Mehrpour, Christopher Hoyte, Abdullah Al Masud, et al.
Expert Opinion on Drug Metabolism & Toxicology (2023) Vol. 19, Iss. 6, pp. 367-380
Closed Access | Times Cited: 3
On the Optimization of Embedding Spaces via Information Granulation for Pattern Recognition
Alessio Martino, Fabio Massimo Frattale Mascioli, Antonello Rizzi
2022 International Joint Conference on Neural Networks (IJCNN) (2020), pp. 1-8
Open Access | Times Cited: 8
An Enhanced Filtering-Based Information Granulation Procedure for Graph Embedding and Classification
Alessio Martino, Antonello Rizzi
IEEE Access (2021) Vol. 9, pp. 15426-15440
Open Access | Times Cited: 8
A Cooperative Coevolutionary Approach to Discretization-Based Feature Selection for High-Dimensional Data
Yu Zhou, Junhao Kang, Xiao Zhang
Entropy (2020) Vol. 22, Iss. 6, pp. 613-613
Open Access | Times Cited: 6
Modelling and Recognition of Protein Contact Networks by Multiple Kernel Learning and Dissimilarity Representations
Alessio Martino, Enrico De Santis, Alessandro Giuliani, et al.
Entropy (2020) Vol. 22, Iss. 7, pp. 794-794
Open Access | Times Cited: 6
Intrusion Detection in Wi-Fi Networks by Modular and Optimized Ensemble of Classifiers: An Extended Analysis
Giuseppe Granato, Alessio Martino, Luca Baldini, et al.
SN Computer Science (2022) Vol. 3, Iss. 4
Closed Access | Times Cited: 4
About Granular Rough Computing—Overview of Decision System Approximation Techniques and Future Perspectives
Piotr Artiemjew
Algorithms (2020) Vol. 13, Iss. 4, pp. 79-79
Open Access | Times Cited: 4
A class-specific metric learning approach for graph embedding by information granulation
Luca Baldini, Alessio Martino, Antonello Rizzi
Applied Soft Computing (2021) Vol. 115, pp. 108199-108199
Closed Access | Times Cited: 3
On Granular Rough Computing: Handling Missing Values by Means of Homogeneous Granulation
Piotr Artiemjew, Krzysztof Ropiak
Computers (2020) Vol. 9, Iss. 1, pp. 13-13
Open Access | Times Cited: 2
CDE++: Learning Categorical Data Embedding by Enhancing Heterogeneous Feature Value Coupling Relationships
Bin Dong, Songlei Jian, Ke Zuo
Entropy (2020) Vol. 22, Iss. 4, pp. 391-391
Open Access | Times Cited: 1
A Multi-objective Optimization Approach for the Synthesis of Granular Computing-Based Classification Systems in the Graph Domain
Luca Baldini, Alessio Martino, Antonello Rizzi
SN Computer Science (2022) Vol. 3, Iss. 6
Closed Access | Times Cited: 1
On Information Granulation via Data Filtering for Granular Computing-Based Pattern Recognition: A Graph Embedding Case Study
Alessio Martino, Enrico De Santis, Antonello Rizzi
SN Computer Science (2023) Vol. 4, Iss. 3
Open Access
Facing Graph Classification Problems by a Multi-agent Information Granulation Approach
Enrico De Santis, Giuseppe Granato, Antonello Rizzi
Studies in computational intelligence (2023), pp. 185-204
Closed Access
Computer-Based Mathematical Algorithms and Conceptual Models of Complex Networks for Evolutionary Computing
Qian Liu
Lecture notes on data engineering and communications technologies (2022), pp. 737-746
Closed Access
Machine Learning for Metabolic Networks Modelling: A State-of-the-Art Survey
Marenglen Biba, Narasimha Rao Vajjhala
Studies in big data (2022), pp. 145-153
Closed Access
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