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Personal profile

Academic Biography

Personal webpage: https://www.scedt.tees.ac.uk/c.angione/

Dr Claudio Angione is a Reader in Computer Science at Teesside University, within the Department of Computer Science and Information Systems.

He currently also holds two Visiting Professor positions at the University of Bari, in Italy, and at KMUTT, in Thailand.

He joined the university in 2015 as a Senior Lecturer, after a PostDoc at the University of Cambridge, and a research intern position at Microsoft Research UK.

He holds a PhD in Computer Science from the University of Cambridge, UK,  awarded in 2015 with a thesis titled "Computational methods for multi-omic models of cell metabolism and their importance for theoretical computer science".

He previously obtained a Degree in Mathematics from the University of Catania, Italy. He also obtained a Higher Education Diploma from the Institute for Advanced Studies of the University of Catania, Italy.

Dr Angione's research group works at the intersection of computer science, mathematics and biology. Research topics include machine/deep learning, biomedical modelling and optimisation, systems biology, genome-scale cell models, statistical big data analytics. He has published more than 50 peer-reviewed papers in leading international conferences and high impact journals. He has recently received several awards for his outstanding academic contributions in the community, including an award by the Italian Embassy for the best research project in the Physical and Engineering Sciences in 2016.

He regularly serves as a reviewer for BBSRC Responsive Mode and MRC Responsive Mode grants. He serves as a Program Committee member for top AI and Mathematical Modelling conferences, and as a reviewer for top Computational Biology journals, including Nature Protocols, Metabolic Engineering, Bioinformatics, Oncotarget, Briefings in Bioinformatics, PLOS Computational Biology, BMC Bioinformatics.

Summary of Research Interests

  • Multi-omic models of cell metabolism
  • Machine and deep learning
  • Cancer metabolism
  • Systems biology of genome-scale models
  • Multi-objective optimization
  • Living organisms as Turing machines

Education/Academic qualification

PhD, University of Cambridge

External positions

Visiting Professor, King Mongkut's University of Technology Thonburi


Visiting Professor, University of Bari


Fingerprint Dive into the research topics where Claudio Angione is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Genes Engineering & Materials Science
Metabolic Networks and Pathways Medicine & Life Sciences
Genome Medicine & Life Sciences
Metabolism Engineering & Materials Science
Bacteria Engineering & Materials Science
Systems Biology Medicine & Life Sciences
Gene Expression Medicine & Life Sciences
Multiobjective optimization Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2016 2021

Research Output 2012 2019

Combining metabolic modelling with machine learning accurately predicts yeast growth rate

Culley, C., Vijayakumar, S., Zampieri, G. & Angione, C., Jun 2019, (Accepted/In press).

Research output: Contribution to conferencePaper

Open Access
Metabolic engineering
Gene expression
Industrial applications
Learning systems
Open Access
Precision Medicine
Systems Biology
61 Downloads (Pure)

Machine and deep learning meet genome-scale metabolic modeling

Zampieri, G., Vijayakumar, S., Yaneske, E. & Angione, C., 11 Jul 2019, In : PLoS Computational Biology. 15, 7, 29 p., e1007084.

Research output: Contribution to journalArticle

Open Access
artificial intelligence
Learning systems
Machine Learning
96 Downloads (Pure)

Social Dynamics Modeling of Chrono-nutrition

Di Stefano, A., Scata, M., Vijayakumar, S., Angione, C., La Corte, A. & Lio, P., 30 Jan 2019, In : PLoS Computational Biology. 15, 1, p. e1006714 e1006714.

Research output: Contribution to journalArticle

Open Access
Social Dynamics
human behavior
Human Behavior
Dynamic Modeling
139 Downloads (Pure)

CiliateGEM: an open-project and a tool for predictions of ciliate metabolic variations and experimental condition design

Mancini, A., Eyassu, F., Conway, M., Occhipinti, A., Lió, P., Angione, C. & Pucciarelli, S., 30 Nov 2018, In : BMC Bioinformatics. 19, (Suppl 15), p. 442-442 1 p.

Research output: Contribution to journalArticle

Open Access
Research Design
Metabolic Network