| A pipeline and comparative study of 12 machine learning models for text classification A Occhipinti, L Rogers, C Angione Expert Systems with Applications 201, 117193, 2022 | 49 | 2022 |
| In silico engineering of Pseudomonas metabolism reveals new biomarkers for increased biosurfactant production A Occhipinti, F Eyassu, TJ Rahman, PKSM Rahman, C Angione PeerJ 6, e6046, 2018 | 29 | 2018 |
| Loss of full-length dystrophin expression results in major cell-autonomous abnormalities in proliferating myoblasts MRF Gosselin, V Mournetas, M Borczyk, S Verma, A Occhipinti, J Róg, ... Elife 11, e75521, 2022 | 27 | 2022 |
| Modelling circulating tumour cells for personalised survival prediction in metastatic breast cancer G Ascolani, A Occhipinti, P Liò PLoS computational biology 11 (5), e1004199, 2015 | 20 | 2015 |
| Cancer markers selection using network-based cox regression: a methodological and computational practice A Iuliano, A Occhipinti, C Angelini, I De Feis, P Lió Frontiers in physiology 7, 208, 2016 | 16 | 2016 |
| Combining pathway identification and breast cancer survival prediction via screening-network methods A Iuliano, A Occhipinti, C Angelini, I De Feis, P Liò Frontiers in genetics 9, 206, 2018 | 15 | 2018 |
| Discovering essential multiple gene effects through large scale optimization: an application to human cancer metabolism A Occhipinti, Y Hamadi, H Kugler, CM Wintersteiger, B Yordanov, ... IEEE/ACM transactions on computational biology and bioinformatics 18 (6 …, 2020 | 14 | 2020 |
| Machine learning methods for survival analysis with clinical and transcriptomics data of breast cancer LMT Doan, C Angione, A Occhipinti Computational biology and machine learning for metabolic engineering and …, 2022 | 7 | 2022 |
| Cosmonet: An r package for survival analysis using screening-network methods A Iuliano, A Occhipinti, C Angelini, I De Feis, P Liò Mathematics 9 (24), 3262, 2021 | 6 | 2021 |
| Meta databases of steel frame buildings for surrogate modelling and machine learning-based feature importance analysis D Samadian, IB Muhit, A Occhipinti, N Dawood Resilient Cities and Structures 3 (1), 20-43, 2024 | 5 | 2024 |
| Mechanism-aware and multimodal AI: beyond model-agnostic interpretation A Occhipinti, S Verma, C Angione Trends in Cell Biology, 2023 | 5 | 2023 |
| Surrogate models for seismic and pushover response prediction of steel special moment resisting frames D Samadian, IB Muhit, A Occhipinti, N Dawood Engineering Structures 314, 118307, 2024 | 3 | 2024 |
| CiliateGEM: an open-project and a tool for predictions of ciliate metabolic variations and experimental condition design A Mancini, F Eyassu, M Conway, A Occhipinti, P Liò, C Angione, ... BMC bioinformatics 19, 123-130, 2018 | 3 | 2018 |
| Bose–Einstein condensation in satisfiability problems C Angione, A Occhipinti, G Stracquadanio, G Nicosia European Journal of Operational Research 227 (1), 44-54, 2013 | 3 | 2013 |
| A Practical Guide to Integrating Multimodal Machine Learning and Metabolic Modeling S Vijayakumar, G Magazzù, P Moon, A Occhipinti, C Angione Computational Systems Biology in Medicine and Biotechnology: Methods and …, 2022 | 2 | 2022 |
| Applications of network-based survival analysis methods for pathways detection in cancer A Iuliano, A Occhipinti, C Angelini, I De Feis, P Lió Computational Intelligence Methods for Bioinformatics and Biostatistics …, 2015 | 2 | 2015 |
| Satisfiability by Maxwell-Boltzmann and Bose-Einstein Statistical Distributions C Angione, A Occhipinti, G Nicosia Journal of Experimental Algorithmics (JEA) 19, 1.4, 2014 | 2 | 2014 |
| Cross-attention enables deep learning on limited omics-imaging-clinical data of 130 lung cancer patients S Verma, G Magazzu, N Eftekhari, T Lou, A Gilhespy, A Occhipinti, ... Cell reports methods 4 (7), 2024 | 1 | 2024 |
| A Computational Model of Cancer Metabolism for Personalised Medicine A Occhipinti, C Angione Building Bridges in Medical Science 2021, 2021 | 1 | 2021 |
| Ablation of the dystrophin Dp71f alternative C-terminal variant increases sarcoma tumour cell aggressiveness N Alnassar, J Hajto, RMH Rumney, S Verma, M Borczyk, C Saha, ... Human Molecular Genetics, ddae094, 2024 | | 2024 |
Claudio AngioneProfessor of Artificial Intelligence, Teesside UniversityEmail verificata su tees.ac.uk
