Projects per year
Personal profile
Academic Biography
Dr Claudio Angione joined Teesside University in 2015 as a Senior Lecturer in Computer Science.
Before joining Teesside, he worked at Microsoft Research in Cambridge and as a Research Associate at the University of Cambridge.
Claudio holds a PhD in Computer Science at the University of Cambridge, UK, 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 Applied 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.
His research interests are at the intersection of computer science, mathematics and biology. They include systems biology of genome-scale models, cancer metabolism, machine learning, multi-objective optimisation, computation with molecular Turing machines, and statistical-physical approaches in satisfiability problems.
Personal webpage: https://www.scm.tees.ac.uk/c.angione/
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
2019Visiting Professor, University of Bari
2019Fingerprint 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.
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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
Machine learning and metabolic modelling of biofilms in the human gut
Angione, C. & Efthimiou, G.
30/05/19 → 29/05/20
Project: Research
QuickFit: Quick fitting of prosthetic sockets for above knee amputees
Gao, J., Ali, Z., Angione, C. & Scott, S.
1/10/18 → 30/09/20
Project: Research
KTP - Mersen UK Teesside Ltd
Hughes, D., Nabhani, F., Zeng, Y. & Angione, C.
1/10/18 → 30/09/20
Project: Other
THYME: Teesside, Hull and York – Mobilising Bioeconomy Knowledge Exchange
Montague, G., Zeng, Y., Angione, C. & Archer, G.
1/04/18 → 31/03/21
Project: Research
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 conference › Paper › Research › peer-review
Open Access
File
Metabolic engineering
Gene expression
Yeast
Industrial applications
Learning systems
Human systems biology and metabolic modelling: a review - from disease metabolism to precision medicine
Angione, C., 10 Jun 2019, In : BioMed Research International.Research output: Contribution to journal › Article › Research › peer-review
Open Access
File
Precision Medicine
Systems Biology
Metabolism
Medicine
Genes
Machine and deep learning meet genome-scale metabolic modelling
Zampieri, G., Vijayakumar, S., Yaneske, E. & Angione, C., 11 Jul 2019, In : PLoS Computational Biology. 15, 7, 29 p., e1007084.Research output: Contribution to journal › Article › Research › peer-review
Open Access
File
artificial intelligence
Learning systems
Machine Learning
Genome
learning
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 journal › Article › Research › peer-review
Open Access
File
Social Dynamics
human behavior
Nutrition
Human Behavior
Dynamic Modeling
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. 442-442Research output: Contribution to journal › Article › Research › peer-review
Open Access
File
Metabolism
Research Design
Glucose
Metabolic Network
Prediction