Computer Laboratory


(Here photos on Cambridge exam "lifestyle")

Pietro Lio'

I am Full Professor of Computational Biology at the department of Computer Science and Technology of the University of Cambridge and I am a member of the Artificial Intelligence group.
I have a MA from Cambridge, a PhD in Complex Systems and Non Linear Dynamics (School of Informatics, dept of Engineering of the University of Firenze, Italy) and a PhD in (Theoretical) Genetics (University of Pavia, Italy).
Other Affliations: I am member of - the Integrate Cancer Medicine Institute,  the committee of MPhil in Computational Biology (Stakeholder Group for the CCBI) , steering committee of Cambridge BIG dataVPH-UK (Virtual Physiologycal Human), Fellow of Clare Hall College. I am Listed in
Dept Administrative duties: reviewer in University of Cambridge complaint and review procedure committee; Advanced Computing MPhil and PartIII examiner; others:  External Examiner at the University of Newcastle for the MSc Bioinformatics, MSc Computational Neuroscience and Neuroinformatics, MSc Computational Systems Biology. 
I have successfully completed the equality and diversity essentials.

My research interest focuses on using bioinformatics, computational biology models and machine learning to integrate various types of data (molecular and clinical, drugs, social and lifestyle) across different spatial and temporal scales of biological complexity to address personalised and precision medicine. In the context of basic science, these approaches are effective in understanding the mechanisms and the dynamics of how biological elements build up properties such as sensing the environment, information carrying, being programmable and doing computation and communication. In the context of biomedical fields, by integrating different layers of evidences, predictive models will improve the accuracy of diagnosis of complex diseases in presence of other chronic and acute conditions, will identify effective markers for disease trajectory and suggest composition of treatments (drugs and lifestyle) before the manifestation of symptoms.

I am happy to receive enquiries for PhD applications. Office: FC20; tel: +44 (0)1223-763604; E_mail: Pietro.Lio at


Recent papers (2017-2019), Full list of Publications

Machine Learning and Bioinformatics Methods for Computational medicine, Big Health Data Integration and comorbidities

Ascolani G, Lio' P, Modeling breast cancer progression to bone: how driver mutation order and metabolism matter.  BMC Medical Genomics

S. Pernice, L. Follia, G. Balbo, L. Milanesi, G. Sartini, N. Totis, P. Lio I. Merelli, F. Cordero and M. Beccuti. Integrating Petri nets and Flux Balance methods in computationalbiology models: a methodological and computational practice. Fundamenta Informaticae (To be published)

Vikash Singh and Pietro Lio' Unsupervised Approaches Harnessing Graph Neural Networks for Disease-Gene Prediction for the Workshop on Computational Biology being held on June 14, 2019 at the ICML conference

Drug-Drug Adverse Effect Prediction with Graph Co-Attention for the Workshop on Computational Biology being held on June 14, 2019 at the ICML conference

Emanuele Rossi, Federico Monti, Michael Bronstein, Pietro Liò, ncRNA Classification with Graph Convolutional Networks, arXiv:1905.06515 

Simeon E. Spasov, Pietro Lio', Dynamic Neural Network Channel Execution for Efficient Training, arXiv:1905.06435 

Enxhell Luzhnica, Ben Day, Pietro Liò, On Graph Classification Networks, Datasets and Baselines, accepted

Tiago Azevedo, Luca Passamonti, Pietro Lio, Nicola Toschi, A machine learning tool for interpreting differences in cognition using brain features, bioRxiv 558403; doi:

HL Smith, A Stevens, B Minogue, S Sneddon, L Shaw, L Wood, T Adeniyi, ...
Systems based analysis of human embryos and gene networks involved in cell lineage allocation
BMC genomics 20 (1), 171, 2019

A Deac, YH Huang, P Veličković, P Liò, J Tang, Drug-Drug Adverse Effect Prediction with Graph Co-Attention
arXiv preprint arXiv:1905.00534,  2019

Md H Rahman, S Peng, C Chen, P Lio', M.A Moni, Genetic effect of type 2 Diabetes to the progression of Neurological Diseases, bioRxiv 480400; doi:

HK Rana, MR Akhtar, MB Islam, MB Ahmed, P Lio, JMW Quinn, F Huq, ..., Genetic effects of welding fumes on the development of respiratory system diseases, Computers in biology and medicine 108, 142-149, 2019

L Xiaofeng, J Fangshuo, Z Xiao, Y Shengwei, S Jing, P Lio', ASSCA: API Sequence and Statistics Features Combined Architecture For Malware Detection, Computer Networks, 2019

A Di Stefano, M Scatà, A La Corte, SK Das, P Liò, Improving QoE in Multi-layer Social Sensing: A Cognitive Architecture and Game Theoretic Model,  Proceedings of the Fourth International Workshop on Social Sensing, 18-23

FL Opolka, A Solomon, C Cangea, P Veličković, P Liò, RD Hjelm, Spatio-Temporal Deep Graph Infomax,
arXiv preprint arXiv:1904.06316

PL Spyridon Bakas, Mauricio Reyes, Andras Jakab et al. , Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge, 49, 2019

J Zhu, G Yang, P Lio', Lesion focused super-resolution, Medical Imaging 2019: Image Processing 10949, 109491L, 2019

D Wang, M Jamnik, P Lio', Unsupervised extraction of interpretable graph representations from multiple-object scenes, accepted at ICML 2019.

D Wang, M Jamnik, P Lio', Unsupervised and interpretable scene discovery with Discrete-Attend-Infer-Repeat, arXiv preprint arXiv:1903.06581, 2019

HK Rana, MR Akhtar, MB Ahmed, P Lio, JMW Quinn, F Huq, MA Moni, Genetic effects of welding fumes on the progression of neurodegenerative diseases, Neurotoxicology 71, 93-101, 2019

R Vignani, P Liò, M Scali, How to integrate wet lab and bioinformatics procedures for wine DNA admixture analysis and compositional profiling: Case studies and perspectives, PloS one 14 (2), e0211962, 2019

A Di Stefano, M Scatà, S Vijayakumar, C Angione, A La Corte, P Liò Social dynamics modeling of chrono-nutrition, PLoS computational biology 15 (1), e1006714, 2019

AG Rakowski, P Veličković, E Dall'Ara, P Liò ChronoMID-Cross-Modal Neural Networks for 3-D Temporal Medical Imaging Data, arXiv preprint arXiv:1901.03906

J Zhu, G Yang, P Lio' How Can We Make GAN Perform Better in Single Medical Image Super-Resolution? A Lesion Focused Multi-Scale Approach, arXiv preprint arXiv:1901.03419

T Azevedo, L Passamonti, P Lio, N Toschi A machine learning tool for interpreting differences in cognition using brain features, BioRxiv, 558403

T Muller, P Lio' Personalisable Clinical Decision Support System, ERCIM NEWS, 19-20, 2019

MD Ganggayah, NA Taib, YC Har, P Lio, SK Dhillon, Predicting factors for survival of breast cancer patients using machine learning techniques, BMC medical informatics and decision making 19 (1), 48

Petar Veličković, William Fedus, William L. Hamilton, Pietro Lio', Yoshua Bengio, R Devon Hjelm Deep Graph Infomax.

Haider S. at al. Pathway-Based Subnetworks Enable Cross-Disease Biomarker Discovery. In press on Nature Communications.

Editing a Springer Book on Automated Reasoning in Systems Biology and Medicine with Paolo Zuliani

J. Despeyroux, A. Felty, P. Lio’, C. Olarte A Logical Framework for Modelling Breast tumorigenesis. submitted to International Symposium on Molecular Logic and Computational Synthetic Biology.

Hui Xiao, Krzysztof Bartoszek and Pietro Lio'. Multi-omic analysis of signaling factors in inflammatory comorbidities. BMC Bioinformatics

Ioana Bica, Petar Velickovi ́c, Hui Xiao and Pietro Lio' (2018) Multi-omics data integration using cross-modal neural networks ESANN 2018 proceedings, European Symposium on Artificial Neural Networks, Computational  Intelligence  and Machine Learning.  Bruges (Belgium), 25-27 April 2018

Eugenio Del Prete, Angelo Facchiano, Pietro Lio'.  Bioinformatics methodologies for coeliac disease and its comorbidities .

Marco Barsacchi, Helena Andres-Terre, Pietro Lio' GEESE: Metabolically driven latent space learning for gene expression data. Bioarxiv.

Francesco Bardozzo, Pietro Lio' and Roberto Tagliaferri (2018) A study on multi-omic oscillations in Escherichia coli metabolic networks. BMC Bioinformatics201819 (Suppl 7) :194.

I Saggese, E Bona, M Conway, F Favero, M Ladetto, P Lio', G Manzini (2018) Flavio Mignone STAble: a novel approach to de novo assembly of RNA-seq data and its application in a metabolic model network based metatranscriptomic workflow BMC bioinformatics 19 (7), 184

Mancini et al. CiliateGEM: an open-project for ciliates metabolism analysis with Tetrahymena thermophila as model. A tool for predictions of metabolic variations and experimental condition design (BMC Bioinformatics, in press).

Andrea Tangherloni, Simone Spolaor, Leonardo Rundo, Marco S. Nobile, Paolo Cazzaniga, Giancarlo Mauri, Pietro Lio', Ivan Merelli, Daniela Besozzi GenHap: A Novel Computational Method Based on Genetic Algorithms for Haplotype Assembly BMC Bioinformatics

Zakaria Benmounah et al., Parallel Swarm Intelligence Strategies for Large-scale Clustering based on MapReduce with Application to Epigenetics of Aging Applied Soft Computing

Edgar Liberis Petar Velickovic, Pietro Sormanni, Michele Vendruscolo and Pietro Lio' (2018) Parapred: Antibody Paratope Prediction using Convolutional and Recurrent Neural Networks. Bioinformatics 2018 Apr 16. doi: 10.1093/bioinformatics/bty305.

Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio', Yoshua Bengio Graph Attention Networks. accepted at ICLR 2018

Scatà M, Di Stefano A, La Corte A, Lio' P. (2018) Quantifying the propagation of distress and mental disorders in social networks. Sci Rep. 2018 Mar 22;8(1):5005. doi: 10.1038/s41598-018-23260-2.

Duo Wang, Mateja Jamnik, Pietro Lio' (2018)  Investigating diagrammatic reasoning with deep
neural networks. Accepted at Diagrams 2018

Peng He, Tadashi Nakano, Yuming Mao, Pietro Lio', Qiang Liu, Kun Yang (2018) Stochastic Channel Switching of Frequency-Encoded Signals in Molecular Communication Networks. IEEE Communications Letters 22(2): 332-335 (2018)

Ezio Bartocci, Pietro Lio', Nicola Paoletti Guest Editors' Introduction to the Special Section on the 14th International Conference on Computational Methods in Systems Biology (CMSB 2016). IEEE/ACM Trans. Comput. Biology Bioinform. 15(4): 1122-1123 (2018)

Akhil Mathur, Tianlin Zhang, Sourav Bhattacharya, Petar Velickovic, Leonid Joffe, Nicholas D. Lane, Fahim Kawsar, Pietro Lio' (2018) Using deep data augmentation training to address software and hardware heterogeneities in wearable and smartphone sensing devices. IPSN 2018: 200-211

Petar Veličković, Laurynas Karazija, Nicholas D. Lane, Sourav Bhattacharya, Edgar Liberis, Pietro Liò, Angela Chieh, Otmane Bellahsen, Matthieu Vegreville (2017) Cross-modal Recurrent Models for Human Weight Objective Prediction from Multimodal Time-series Data. NIPS ML4H & NIPS TSW

Momchil Peychev, Petar Velickovic, Pietro Lio' (2017) Quantifying the Effects of Enforcing Disentanglement on Variational Autoencoders. 2017 NIPS Workshop on Learning Disentangled Representations

Emmanouil I Athanasiadis, Helena Andres, Jan G Botthof, Lauren Ferreira, Pietro Lio', Ana Cvejic (2017). Single-cell RNA-Sequencing uncovers transcriptional states and fate decisions in haematopoiesis. Nature Communications

Laurynas Karazija, Petar Velickovic, Pietro Lio' (2018)  Automatic Inference of Cross-Modal Connection Topologies for X-CNNs. ISNN 2018: 54-63

Vijayakumar S., Conway M., Lio' P. and Angione C. (2017) Multi-omic genome-scale models: methodologies, hands-on and perspectives. Springer Verlag

F. Tordini et al. (2017) Scientific Workflows on Clouds with Heterogeneous and Preemtible Instances. Proceedings ParCO

Bianchi L, Lio' P. Opportunities for community awareness platforms in personal genomics and bioinformatics education. Brief Bioinform. 2017 Nov 1;18(6):1082-1090. doi: 10.1093/bib/bbw078

Martins DP, Barros MT, Pierobon M, Kandhavelu M, Lio' P, Balasubramaniam S. (2017) Computational Models for Trapping Ebola Virus Using Engineered Bacteria. IEEE/ACM Transactions on Computational Biology and Bioinformatics

Brouwer T. and Lio' P. (2017) Bayesian Hybrid Matrix Factorisation for Data Integration. Accepted at AISTATS 2017; PMLR 54:557-566

Vijayakumar S. Conway M., Lio' P. and Angione C. (2017) Seeing the wood for the trees: a forest of methods for omic-network integration in metabolic modelling. Briefings in Bioinformatics

Brouwer T. and Lio' P. (2017) Comparative Study of Inference Methods for Bayesian Matrix Factorisation. Accepted at ECML-PKDD 2017 (LNCS)

F. Tordini, I. Merelli, P. Lio', L. Milanesi, M. Aldinucci:  NuchaRt: Embedding High-Level Parallel Computing in R for Augmented Hi-C Data Analysis. Computational Intelligence Methods for Bioinformatics and Biostatistics Volume 9874 of the series Lecture Notes in Computer Science pp 259-272

M Barandalla, H Shi, H Xiao, S Colleoni, C Galli, P Lio', M. Trotter and G Lazzari (2017) Global gene expression profiling and senescence biomarker analysis of hESC exposed to H2O2 induced non-cytotoxic oxidative stress Stem Cell Research & Therapy 20178:160, DOI: 10.1186/s13287-017-0602-6

Moni M and Liò P. (2017) Genetic Profiling and Comorbidities of Zika Infection. Journal of Infectuous diseases (in Press).

Oshota et al. (2017) Transcriptome and Proteome Analysis of Salmonella enterica Serovar Typhimurium Systemic Infection of Wild Type and Immune-deficient Mice. Accepted in Plos One.

Heffernan K. , Lio' P. and Teufel S. (2017) Multilayer Data and Document Stratification for Comorbidity Analysis (2017) Thirteenth International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics. LNBI

Dimitri MG and and Liò P. (2017) DrugClust: a machine learning approach for drugs side effects prediction. Computational Biology and Chemistry (10.1016/j.compbiolchem.2017.03.008).

S Saheb Kashaf,  C. Angione, P. Lio' (2017) Making life difficult for Clostridium difficile: augmenting the pathogen's metabolic model with transcriptomic and codon usage data for better therapeutic target characterization. BMC Systems Biology.

Felicetti L, et al. Lio' P. (2017) A big-data layered architecture for analyzing molecular communications systems in blood vessels. Accepted at ACM NanoCom 2017

Veličković P., Wang, D., Lane N., Lio', P.  (2017)  X-CNN: Cross-modal Convolutional Neural Networks for Sparse Datasets. IEEE SSCI 2016 (

Scatà M., Di Stefano A., La Corte A., Lio' P. (2016) The Impact of Heterogeneity and Awareness in Modeling Epidemic Spreading on Multiplex Networks, Scientific Reports 6, Article number: 37105

Machine Learning Methods in Image Analysis and Neuroinformatics

Spasov Simeon et al., A Multi-modal Convolutional Neural Network Framework for the Prediction of Alzheimer Disease, 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'18)

Duo Wang, Rui Zhang, Jin Zhu, Zhongzhao Teng, Yuan Huang, Filippo Spiga, Michael Hong-Fei Du, Jonathan H. Gillard, Qingsheng Lu, Pietro Lio' (2018) Neural network fusion: a novel CT-MR aortic aneurysm image segmentation method. Medical Imaging: Image Processing 2018: 1057424

Jin Zhu, Duo Wang Pietro Lio' (2017) A Multi-pathway 3D Dilated Convolutional Neural Network for Brain Tumor Segmentation. BRATS challenge

G M Dimitri S Agrawal Adam Young J Donnelly P Smielewski, P. Hutchinsons, M. Czosnyka, P Lio' C. Haubrich (2017) A multiplex network approach for the analysis of Intracranial Pressure and Heart Rate data in traumatic brain injured patients. Applied Network Science

Dimitri MG. et al., Computational challenges for the analysis of Intracranial Pressure and Heart Rate data in traumatic brain injuries patients.  Frontiers, (neuroinformatic workshop in Reading).


2018 - BITS Bioinformatics Italian Society- Torino
2016: The paper “Bioaccumulation modelling and sensitivity analysis for discovering key players in contaminated food webs: The case study of PCBs in the Adriatic Sea” (M. Taffi first author) has won the 2016 BYRA first prize at ISEM (The International Society for Ecological Modelling Global Conference) 2016 and the MCED (Modelling Complex Ecological Dynamics) 2016 Award second prize.
2013 - Lagrange Fellowship (ISI, Universita' Piemonte Orientale)

2012 - Best Paper (Computing with MetabolicMachines) at Turing 100 in Manchester (first author Claudio Angione)

2011 - 3rd prize awarded by the European Commission (sponsored by ERCIM) for the  "Methodological bridges for complex systems" (with E. Merelli and N. Paoletti) at the FET 11, 2011  - Future and Emerging Technologies Conference ('Science Beyond Fiction')' conference  - Budapest

Public Engagement

I am active in science communication, and engage often with the media and in public science events (science cafe', European Researchers' Night, Coding Academy, etc). This is very important as a scientist is fundamentally a visionary who needs to interact with society.