Claudio Angione

2.1k total citations
72 papers, 1.3k citations indexed

About

Claudio Angione is a scholar working on Molecular Biology, Biomedical Engineering and Artificial Intelligence. According to data from OpenAlex, Claudio Angione has authored 72 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Molecular Biology, 12 papers in Biomedical Engineering and 5 papers in Artificial Intelligence. Recurrent topics in Claudio Angione's work include Microbial Metabolic Engineering and Bioproduction (38 papers), Bioinformatics and Genomic Networks (21 papers) and Gene Regulatory Network Analysis (19 papers). Claudio Angione is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (38 papers), Bioinformatics and Genomic Networks (21 papers) and Gene Regulatory Network Analysis (19 papers). Claudio Angione collaborates with scholars based in United Kingdom, Italy and United States. Claudio Angione's co-authors include Guido Zampieri, Supreeta Vijayakumar, Elisabeth Yaneske, Píetro Lió, Eric Silverman, Pattanathu Rahman, Giuseppe Magazzù, Giuseppe Nicosia, Jole Costanza and Filmon Eyassu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Claudio Angione

67 papers receiving 1.3k citations

Peers

Claudio Angione

RNMI

Lili Niu China

Kaveh Kavousi Iran

Michael Schneider Germany

Lars J. Kangas United States

Pei Zhao China

Zijing Liu China

Wei‐Chun Kao Taiwan

Chuang Ma China

Yusen Zhang China

Fei Feng China

Lili Niu China

Claudio Angione

716 ×0.8

108 ×0.5

80 ×0.8

97 ×1.0

25 ×0.5

RNMI

Citations per year, relative to Claudio Angione Claudio Angione (= 1×) peers Lili Niu

Countries citing papers authored by Claudio Angione

Since Specialization

Citations

This map shows the geographic impact of Claudio Angione's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Claudio Angione with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Claudio Angione more than expected).

Fields of papers citing papers by Claudio Angione

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Claudio Angione. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Claudio Angione. The network helps show where Claudio Angione may publish in the future.

Co-authorship network of co-authors of Claudio Angione

This figure shows the co-authorship network connecting the top 25 collaborators of Claudio Angione. A scholar is included among the top collaborators of Claudio Angione based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Claudio Angione. Claudio Angione is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Angione, Claudio, et al.. (2025). From bulk to single-cell and spatial data: An AI framework to characterise breast cancer metabolic dysregulations across modalities. Computers in Biology and Medicine. 198(Pt B). 111195–111195.

Eftekhari, N, et al.. (2025). Artificial Intelligence in Gynaecology Oncology. BJOG An International Journal of Obstetrics & Gynaecology. 133(4).

Islam, Meez, et al.. (2024). Uncovering potential diagnostic and pathophysiological roles of α‐synuclein and DJ‐1 in melanoma. Cancer Medicine. 13(1). e6900–e6900. 5 indexed citations

Zampieri, Guido, Léa Cabrol, Eduardo Castro‐Nallar, et al.. (2024). Microbiome alterations are associated with apolipoprotein E mutation in Octodon degus and humans with Alzheimer’s disease. iScience. 27(8). 110348–110348. 6 indexed citations

Zampieri, Guido, et al.. (2023). Multi-dimensional experimental and computational exploration of metabolism pinpoints complex probiotic interactions. Metabolic Engineering. 76. 120–132. 14 indexed citations

Angione, Claudio, Priyanka Dey, Tuomo Polvikoski, et al.. (2023). Glycosylation spectral signatures for glioma grade discrimination using Raman spectroscopy. BMC Cancer. 23(1). 174–174. 16 indexed citations

Sopić, Miron, Emma Robinson, Costanza Emanueli, et al.. (2023). Integration of epigenetic regulatory mechanisms in heart failure. Basic Research in Cardiology. 118(1). 16–16. 13 indexed citations

Nnyanzi, Lawrence Achilles, Akinyele Olumuyiwa Adisa, Kehinde Kazeem Kanmodi, et al.. (2023). Status of Omics Research Capacity on Oral Cancer in Africa: A Systematic Scoping Review Protocol. SHILAP Revista de lepidopterología. 3(2). 327–338.

Polvikoski, Tuomo, George S. Karagiannis, Claudio Angione, et al.. (2022). The diagnostic and prognostic potential of the EGFR/MUC4/MMP9 axis in glioma patients. Scientific Reports. 12(1). 19868–19868. 11 indexed citations

10.

Vijayakumar, Supreeta, et al.. (2022). A Practical Guide to Integrating Multimodal Machine Learning and Metabolic Modeling. Methods in molecular biology. 2399. 87–122. 5 indexed citations

11.

Short, Michael, et al.. (2021). An Integrated Approach to Adaptive Control and Supervisory Optimisation of HVAC Control Systems for Demand Response Applications. Energies. 14(8). 2078–2078. 11 indexed citations

12.

Robinson, Emma, Andrew H. Baker, Mairi Brittan, et al.. (2021). Dissecting the transcriptome in cardiovascular disease. Cardiovascular Research. 118(4). 1004–1019. 24 indexed citations

13.

Zampieri, Guido, et al.. (2021). Modeling Customer Experience in a Contact Center through Process Log Mining. ACM Transactions on Intelligent Systems and Technology. 12(4). 1–21. 2 indexed citations

14.

Vijayakumar, Supreeta, Pattanathu Rahman, & Claudio Angione. (2020). A Hybrid Flux Balance Analysis and Machine Learning Pipeline Elucidates Metabolic Adaptation in Cyanobacteria. iScience. 23(12). 101818–101818. 45 indexed citations

15.

Yaneske, Elisabeth & Claudio Angione. (2018). The poly-omics of ageing through individual-based metabolic modelling. BMC Bioinformatics. 19(S14). 415–415. 22 indexed citations

16.

Vijayakumar, Supreeta, et al.. (2017). Seeing the wood for the trees: a forest of methods for optimization and omic-network integration in metabolic modelling. Briefings in Bioinformatics. 19(6). 1218–1235. 35 indexed citations

17.

Kashaf, Sara Saheb, Claudio Angione, & Píetro Lió. (2017). Making life difficult for Clostridium difficile: augmenting the pathogen’s metabolic model with transcriptomic and codon usage data for better therapeutic target characterization. BMC Systems Biology. 11(1). 25–25. 17 indexed citations

18.

Angione, Claudio, et al.. (2015). Analysis and design of molecular machines. Theoretical Computer Science. 599. 102–117. 3 indexed citations

19.

Angione, Claudio & Píetro Lió. (2015). Predictive analytics of environmental adaptability in multi-omic network models. Scientific Reports. 5(1). 15147–15147. 39 indexed citations

20.

Angione, Claudio, et al.. (2013). A design automation framework for computational bioenergetics in biological networks. Molecular BioSystems. 9(10). 2554–2564. 7 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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