Projects per year
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
2019Visiting Professor, University of Bari
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Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Projects
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
Machine learning and metabolic modelling of biofilms in the human gut
Angione, C. & Efthimiou, G.
30/05/19 → 29/05/20
Project: Research
Research Output
Discovering Essential Multiple Gene Effects through Large Scale Optimization: an Application to Human Cancer Metabolism
Occhipinti, A., Hamadi, Y., Kugler, H., Wintersteiger, C., Yordanov, B. & Angione, C., 2 Apr 2020, In : IEEE/ACM Transactions on Computational Biology and Bioinformatics.Research output: Contribution to journal › Article
Open Access
File
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
Open Access
File
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
Open Access
File
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 journal › Article
Open Access
File
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
Open Access
File