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Claudio Angione
Claudio Angione
Professor of Artificial Intelligence, Teesside University
Email verificata su tees.ac.uk - Home page
Titolo
Citata da
Citata da
Anno
Machine and deep learning meet genome-scale metabolic modelling
G Zampieri, S Vijayakumar, E Yaneske, C Angione
PLoS Computational Biology 15 (7), e1007084, 2019
1482019
Seeing the wood for the trees: a forest of methods for optimisation and omic-network integration in metabolic modelling
S Vijayakumar, M Conway, P Li, C Angione
Briefings in Bioinformatics, 2017
145*2017
Robust design of microbial strains
J Costanza, G Carapezza, C Angione, P Li, G Nicosia
Bioinformatics 28 (23), 3097-3104, 2012
642012
Multiplex methods provide effective integration of multi-omic data in genome-scale models
C Angione, M Conway, P Li
BMC bioinformatics 17 (4), 257-269, 2016
562016
Human Systems Biology and Metabolic Modelling: A Review—From Disease Metabolism to Precision Medicine
C Angione
BioMed Research International 2019, 2019
552019
Predictive analytics of environmental adaptability in multi-omic network models
C Angione, P Li
Scientific reports 5, 2015
522015
A mechanism-aware and multiomic machine-learning pipeline characterizes yeast cell growth
C Culley, S Vijayakumar, G Zampieri, C Angione
Proceedings of the National Academy of Sciences 117 (31), 18869-18879, 2020
282020
Making life difficult for Clostridium difficile: augmenting the pathogen’s metabolic model with transcriptomic and codon usage data for better therapeutic target characterization
SS Kashaf, C Angione, P Li
BMC systems biology 11 (1), 1-13, 2017
242017
Making life difficult for Clostridium difficile: augmenting the pathogen’s metabolic model with transcriptomic and codon usage data for better therapeutic target characterization
SS Kashaf, C Angione, P Li
BMC systems biology 11 (1), 1-13, 2017
242017
Integrating splice-isoform expression into genome-scale models characterizes breast cancer metabolism
C Angione
Bioinformatics 34 (3), 494–501, 2018
212018
Bioinformatics Challenges and Potentialities in Studying Extreme Environments
C Angione, P Li, S Pucciarelli, B Can, M Conway, M Lotti, H Bokhari, ...
International Meeting on Computational Intelligence Methods for…, 2016
21*2016
A hybrid of metabolic flux analysis and bayesian factor modeling for multiomic temporal pathway activation
C Angione, N Pratanwanich, P Li
ACS synthetic biology 4 (8), 880-889, 2015
202015
Situating agent-based modelling in population health research
E Silverman, U Gostoli, S Picascia, J Almagor, M McCann, R Shaw, ...
Emerging Themes in Epidemiology 18 (1), 1-15, 2021
192021
The poly-omics of ageing through individual-based metabolic modelling
E Yaneske, C Angione
BMC Bioinformatics 19 (14), 415, 2018
192018
Integrated multi-omics analysis of ovarian cancer using variational autoencoders
MT Hira, MA Razzaque, C Angione, J Scrivens, S Sawan, M Sarker
Scientific reports 11 (1), 1-16, 2021
182021
Modelling pyruvate dehydrogenase under hypoxia and its role in cancer metabolism
F Eyassu, C Angione
Royal Society Open Science 4 (10), 170360, 2017
182017
Modelling pyruvate dehydrogenase under hypoxia
F Eyassu, C Angione
18*
Computational Methods in Systems Biology
L Cardelli, J Despeyroux, R Grosu, J Hillston, E Bartocci, P Li, N Paole, ...
172016
Pareto optimality in organelle energy metabolism analysis
C Angione, G Carapezza, J Costanza, P Li, G Nicosia
IEEE/ACM transactions on computational biology and bioinformatics 10 (4…, 2013
172013
Optimization of Multi-Omic Genome-Scale Models: Methodologies, Hands-on Tutorial, and Perspectives
S Vijayakumar, M Conway, P Li, C Angione
Metabolic Network Reconstruction and Modeling, 389-408, 2018
162018
Il sistema al momento non pu eseguire l'operazione. Riprova pi tardi.
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