Pietro Lio'
Department of Computing science & Technology

Head of the Computational Biology Group at the Computer Lab, Pietro is an expert in advanced machine learning and artificial intelligence techniques. Pietro's lab develops methods for combining multi-omics and multi-physics models of living systems spanning multiple scales and encompassing interactions from molecules to cells to tissues to organ. He also develops and tests methodologies for modeling biomedical systems


Computer Laboratory website



Lab members

Research Associate
Dr Gianluca Ascolani

PhD Students
Hui Xiao
Max Conway
Helena Andrés Terre
Giovanna Maria Dimitri
Pablo Spivakovsky-González
Petar Veličković
Tiago Azevedo
Simeon Spasov
Duo Wang
Jin Zhu
Cătălina Cangea
Benjamin Day
Emma Rocheteau

Master's Students
Razvan Kusztos
Nathaniel McAleese-Park
Miloš Stanojević 
Ioana Bica
Michelle Zheng

Undergraduate Students
Andreea-Ioana Deac
Marko Stanković
Andrew Wells

Selected recent publications:

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

I. Bica, Petar Veličković, Hui Xiao and Pietro Liò (2018) Multi-omics data integration using cross-modal neural networks. Accepted at ESANN

Wang D. et al. (2017) Neural network fusion: a novel CT-MR Aortic Aneurysm image segmentation method. accepted  at SPIE medical imaging conference 2018 

Jin Zhu, Duo Wang Pietro Liò (2017) A Multi-pathway 3D Dilated Convolutional Neural Network for Brain Tumor SegmentationBRATS challenge 

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 Liò (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

Peng He , Tadashi Nakano , Yuming Mao, Lio’ Pietro, Qiang Liu, and Kun Yang (2017) Stochastic Channel Switching of Frequency-encoded Signals in Molecular Communication Networks. IEEE COMMUNICATIONS LETTERS

Vijayakumar S., Conway M., Liò 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

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

G M Dimitri et al (2017) A multiplex network approach for the analysis of Intracranial Pressure and Heart Rate data in traumatic brain injured patients. Applied Network Science

Brouwer T. and Liò P. (2017) Bayesian Hybrid Matrix Factorisation for Data Integration. Accepted at AISTATS 2017; PMLR 54:557-566 

Vijayakumar S. Conway M., Liò 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 Liò P. (2017) Comparative Study of Inference Methods for Bayesian Matrix Factorisation.Accepted at ECML-PKDD 2017 (LNCS)

F. Tordini, I. Merelli, P. Liò, 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

Tordini F., Aldinucci M., Milanesi L., Pietro Liò, Merelli I. The genome conformation as an integrator of multi-omic data: the example of damage spreading in cancer. Frontiers in Genetics.

Veličković P., Wang, D., Lane N., Lio', P.  (2016)  X-CNN: Cross-modal Convolutional Neural Networks for Sparse Datasets. IEEE SSCI 2016 (http://ssci2016.cs.surrey.ac.uk/)

Tordini F., Drocco M., Misale C., Milanesi L., Lio` P., Merelli I., Torquati, M and Aldinucci M., NuChart-II: The road to a fast and scalable tool for Hi-C data analysis. The International Journal of High Performance Computing Applications 1–16, 2016.

Brouwer T., Frellsen J. and Liò P. (2016) Fast Bayesian Non-Negative Matrix Factorisation and Tri-Factorisation. NIPS Workshop on Advances in Approximate Bayesian Inference , Barcelona  arXiv:1610.08127

Pratanwanich N., Liò P. , Stegle O. (2016). Warped Matrix Factorisation for Multi-View Data Integration. Accepted at ECMLPKDD2016.

Angione C, Conway M. and Pietro Lio' (2016) Multiplex methods provide effective integration of multi-omic data in genome-scale models. BMC Bioinformatics. 17 Suppl 4:83. doi: 10.1186/s12859-016-0912-1.

Smedley et al. (2015) The BioMart Community Portal: an innovative alternative to large, centralized data repositories. Nucleic Acids Research, Apr 20. pii: gkv350. 

Shavit, Y., Merelli I, Milanesi L. & Lio', P. (2015)  How computer science can help in understanding the 3D genome architecture. Briefings in Bioinformatics. pii: bbv085

Shavit Y., Walker B., Lio' P (2015) Hierarchical block matrices as efficient representations of chromosome topologies and their application for 3C data integration. Bioinformatics 2015 Dec 17. pii: btv736.

Bardozzo F, Lio P and Tagliaferri R, (2015) Multi omic oscillations in bacterial pathways. IJCNN2015, Dublin.

Hamey F., Shavit Y., Maciulyte V., Town C., Lio' P. and Tosi S. (2015) Automated Detection of Fluorescent Probes in Molecular Imaging. Lecture Notes in Computer Science LNCS 8623

I Merelli, F Tordini, M Drocco, M Aldinucci,  P Liò, L Milanesi (2015) Integrating Multi-omics features exploiting Chromosome Conformation Capture data. Frontiers in genetics Feb 11;6:40. doi: 10.3389/fgene.2015.00040. eCollection 2015.

M Fondi, P Liò (2015) Multi-omics and metabolic modelling pipelines: challenges and tools for systems microbiology. Microbiological Research Feb;171:52-64. doi: 10.1016/j.micres.2015.01.003. Epub 2015 Jan 7.

Shavit, Y., Hamey F. & Lio', P. (2014) FisHical: an R package for iterative FISH-based calibration of Hi-C data. Bioinformatics Jul 23. pii: btu491.

Shavit, Y., & Lio', P. (2014). Combining wavelet changepoint and Bayes Factor for analysing chromosomal interactions data. Molecular BioSystems 10(6):1576-85.

Taffi M., Paoletti N., Liò P., Pucciarelli S., Marini M. (2015) Bioaccumulation modelling and sensitivity analysis for discovering key players in contaminated food webs: the case study of PCBs in the Adriatic Sea.  Ecological Modelling 306:205-215 04 Jun 2015       doi:10.1016/j.ecolmodel.2014.11.030 (Best Young Researcher Award at ISEM 2016).

Taffi, M., Paoletti, N. , Angione, C., Pucciarelli, S., Marini, M., Liò, P. (2014) Bioremediation in marine ecosystems: a computational study combining ecological modelling and flux balance analysis. Frontiers in Genetics, section Systems Biology.  5: 319.Published online Sep 12, 2014. doi:  10.3389/fgene.2014.00319 (see also related editorial).

F. Tordini, M. Drocco, C. Misale, L. Milanesi, P. Liò, I. Merelli, and M. Aldinucci, Parallel Exploration of the Nuclear Chromosome Conformation with NuChart-II, in Proc. of Intl. Euromicro PDP 2015: Parallel Distributed and network-based Processing, Turku, Finland, 2015. 

F. Tordini, M. Drocco, C. Misale, P. Liò, I. Merelli, M. Aldinucci: NuChart-II: the road to a fast and scalable tool for Hi-C data analysis, in International Journal of High Performance Computing Application, 2015.

F. Tordini, I. Merelli, P. Liò, M. Aldinucci and L. Milanesi: NuchaRt: embedding High-Performance Computing in R for augmented DNA Exploration, in Proc. of the 12th Intl. meeting on Computational Intelligence methods for Bionformatics and Biostatistics (CIBB), Naples, Italy, 2015. 

M. Drocco, C. Misale, G. P. Pezzi, F. Tordini, and M. Aldinucci (2015) Memory-Optimised Parallel Processing of Hi-C Data, in Proc. of Intl. Euromicro PDP 2015: Parallel Distributed and network-based Processing, Turku, Finland, 2015

I Merelli, Fabio Tordini, Maurizio Drocco, Marco Aldinucci, Pietro Liò, and Luciano Milanesi. Integrating multi-omic features exploiting chromosome conformation capture data. Frontiers in Genetics, 6(40), 2015

Fabio Tordini, Maurizio Drocco, Claudia Misale, Luciano Milanesi, Pietro Liò, Ivan Merelli, and Marco Aldinucci. Parallel exploration of the nuclear chromosome conformation with NuChart-II. In Proc. of Intl. Euromicro PDP 2015: Parallel Distributed and network-based Processing. IEEE, March 2015.

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

Peng He, Yuming Mao, Qiang Liu, Pietro Liò, Kun Yang, Channel modelling of molecular communications across blood vessels and nerves. ICC 2016: 1-6

Alarcon E. et al, MolComML: The Molecular Communication Markup Language. Accepted at ACM NanoCom 2016.

Reali G. et al. Liò P., (2016) Simulation Tools for Molecular Communications. IEEE TCSIM Newsletter

Felicetti, L., Femminella, M., Reali, G., Lio', P.  (2015)  Applications of molecular communications to medicine: a survey. Nano Communication Networks.