Publications

 N. P. Coles, S. Elsheikh, A. Gouda, A. Quesnel, L. Butler, O. J. Achadu, M. Islam, K. Kalesh, A. Occhipinti, C. Angione, J. Marles-Wright, D. J. Koss, A. J. Thomas, T. F. Outeiro, P. S. Filippou, A. A. Khundakar, "A modified α-synuclein seed amplification assay in Lewy body dementia using Raman spectroscopy and machine learning analysis", Journal of Neuroscience Methods, Volume 425, 2026, 110617, https://www.sciencedirect.com/science/article/pii/S0165027025002614

Doan L.M., Verma, S., Eftekhari, N., Angione, C., & Occhipinti, A. (2025). "From bulk to single-cell and spatial data: An AI framework to characterise breast cancer metabolic dysregulations across modalities." Computers in Biology and Medicine, 198, 111195. https://doi.org/10.1016/j.compbiomed.2025.111195  

Anwar MM, Meseguer S, García-Rodríguez N, Krupinska E, Sele C, Rodríguez-Jiménez A, Verma S, Sagadevan S, Ramon J, Martí R, Occhipinti A., Angione C., Ordóñez‑Morán P., Knecht W., Huertas P., Juanes M. "NK-A 17E-233I: a novel competitive inhibitor of human dihydroorotate dehydrogenase (DHODH) for cancer therapy". Journal of Experimental & Clinical Cancer Research. (2025) Oct 17;44(1):292. https://doi.org/10.1186/s13046-025-03538-w  

Loganathan, P. K., V. Meau-Petit, B. Bhojnagarwala, V. Nair, J. Holmes, A. Occhipinti, and M. Montasser. "Serial lung ultrasound in predicting the need for surfactant and respiratory course in preterm infants—multicentre observational study (SLURP)." European Journal of Pediatrics 184, no. 6 (2025): 356.

Riachy, C., He, M., Joneidy, S., Qin, S., Payne, T., Boulton, G., Occhipinti, A. and Angione, C., 2025. Enhancing deep learning for demand forecasting to address large data gaps. Expert Systems with Applications, 268, p.126200.

Pomeroy, J., Borczyk, M., Kawalec, M., Hajto, J., Carlson, E., Svärd, S., Verma, S., Occhipinti, A. Bareke, E., Boratyńska-Jasińska, A., Dymkowska, D. and Mellado-Ibáñez, A., 2025. Spatiotemporal diversity in molecular and functional abnormalities in the mdx dystrophic brain. Molecular Medicine, 31, p.108.

Coles, N.P., Elsheikh, S., Quesnel, A., Butler, L., Jennings, C., Tarzi, C., Achadu, O.J., Islam, M., Kalesh, K., Occhipinti, A. and Angione, C., 2025. Molecular Insights into α-Synuclein Fibrillation: A Raman Spectroscopy and Machine Learning Approach. ACS Chemical Neuroscience.

Loganathan P., C. Ashton, E. Harrold, S. Wigston, L. Doan, and A. Occhipinti. "Use of real‐time respiratory function monitor improves neonatal face mask ventilation: Cross‐over simulation study." Pediatric Anesthesia 35, no. 1 (2025): 66-74.

Verma, S., Magazzu, G., Eftekhari, N., Lou, T., Gilhespy, A., Occhipinti, A., & Angione, C.  Cross-attention enables deep learning on limited omics-imaging-clinical data of 130 lung cancer patients. Cell reports methods. 2024

A. Occhipinti, Verma S., L.M.T. Doan, and C. Angione. "Mechanism-aware and multimodal AI: beyond model-agnostic interpretation." Trends in Cell Biology. 2023.

L.M.T. Doan, C.Angione, and A. Occhipinti. Machine Learning Methods for Survival Analysis with Clinical and Transcriptomics Data of Breast Cancer. Methods in Molecular Biology. 2023.

A. Occhipinti, L. Rogers, and C. Angione. A pipeline and comparative study of 12 machine learning models for text classification. Expert Systems with Applications, 201, 117193, 2022.

Gosselin, M. R., Mournetas, V., Borczyk, M., Verma, S., A. Occhipinti, Róg, J., ... & Gorecki, D. C. Loss of full-length dystrophin expression results in major cell-autonomous abnormalities in proliferating myoblasts. Elife, 11, e75521. 2022.

A.Iuliano, and A. Occhipinti. Environmental measurements and genetic effects for cancer survival integration data. In 2022 IEEE International Workshop on Metrology for Living Environment (MetroLivEn) (pp. 138-143). IEEE. 2022.

A. Occhipinti, and C. Angione. A Computational Model of Cancer Metabolism for Personalised Medicine. Building Bridges in Medical Science 2021. Cambridge Medical Journal, 2021. [press-release ]

S. Vijayakumar, G. Magazzù, P. Moon, A. Occhipinti and C. Angione. A Practical Guide to Integrating Multimodal Machine Learning and Metabolic Modeling.” Springer Nature Methods in Molecular Biology. 2021.

A. Iuliano, A. Occhipinti, C. Angelini, I. De Feis, and P. Liò, P. Cosmonet: An r package for survival analysis using screening-network methods. Mathematics, 9(24), p.3262. 2021.

A. Occhipinti, Y. Hamadi, H. Kugler, C. Wintersteiger, B. Yordanov and C. Angione. Discovering Essential Multiple Gene Effects through Large Scale Optimization: an Application to Human Cancer Metabolism. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020.

A. Occhipinti, F. Eyassu, T.J. Rahman, P.K.S.M. Rahman and C. Angione, In silico engineering of Pseudomonas metabolism reveals new biomarkers for increased biosurfactant production, PeerJ, 6046, 2018. Featured in Phys.org - In the top 5 most viewed PeerJ Synthetic Biology articles published in 2018.

A. Occhipinti, A. Iuliano, C. Angelini, I. De Feis, and P. Liò, Combining pathway identification and breast cancer survival prediction via screening-network methods, Frontiers in genetics, 2018.

A. Mancini, F. Eyassu, M. Conway, A. Occhipinti, P. Lió, C. Angione, S. Pucciarelli, CiliateGEM: an open-project and a tool for predictions of ciliate metabolic variations and experimental condition design, BMC Bioinformatics, 2018.