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Department of Computer Science and Technology

  • Professor of Computational Biology

I am Full Professor at the department of Computer Science and Technology of the University of Cambridge and I am a member of the Artificial Intelligence group. I am a member of the Cambridge Centre for AI in Medicine.

Background: PhD in Complex Systems and Non Linear Dynamics (School of Informatics, dept of Engineering of the University of Firenze, Italy) and PhD in (Theoretical) Genetics (University of Pavia, Italy). More information is on my personal homepage

Other Affliations: Fellow and member of the Council of Clare Hall College, member of Ellis, the European Lab for Learning & Intelligent Systems, I am member of the Academia Europaea; I am listed in www.topitalianscientists.org/Top_italian_scientists_VIA-Academy.aspx

I am happy to receive enquiries for PhD applications. I have successfully completed the equality and diversity essentials.

Research

My research interest focuses on developing Artificial Intelligence and Computational Biology models to understand diseases complexity and address personalised and precision medicine. Current focus is on Graph Neural Network modeling to build predictive models based on the integration of multi scale, multi omics and multi physics data; integrate deep learning and mechanistic approaches; explainability and interpretability in medicine; exploiting short and long range communications in the human body, between cells and tissues and predict emerging mechanistic properties at systemic medicine level. 

Vision

Develop an AI-based medical digital twin to increase self-awareness; Develop an AI personal decision support system to increase social awareness.

Teaching

  • R250: Graph Neural Networks (ACS MPhil)

Current and Past Postdoctoral students

  • Helena Andres Terre
  • Nikola Simidjievski
  • Zohreh Shams
  • Alessandro di Stefano
  • Gianluca Ascolani
  • Julien Mozziconacci
  • Eric Yu-En Lu

Current and Past PhD students

  • David Buterez
  • Dobrik Georgiev
  • Jacob Moss
  • Pietro Barbiero
  • Cristian Bodnar
  • Alexander Campbell
  • Paris Flood
  • Felix Opolka
  • Ramon Viñas Torné
  • Junwei Yang
  • Paul Scherer
  • Jacob Deasy
  • Catalina Cangea
  • Benjamin Day
  • Emma Rocheteau
  • Tiago Azevedo
  • Simeon Spasov
  • Duo Wang
  • Jin Zhu
  • Petar Velickovic
  • Helena Andres Terre
  • Giovanna maria Dimitri
  • Pablo Spivakovsky-Gonzalez
  • Thomas Brouwer
  • Maxwell Conway
  • Hui Xiao
  • Annalisa Occhipinti
  • Naruemon (Ploy) Pratanwanich
  • Yoli Shavit
  • Claudio Angione
  • Mohammad Ali Moni
  • Syed Haider
  • Stephan Kitchovitch
  • Yuedong Song
  • Ian Leung
  • Viet Anh Nguyen
  • Anilkumar Sorathiya
  • Richard Van der Wath

 

Recent papers at AI Top conferences


Dominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Liò
Directional Graph Networks. ICLM 2021
Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yu Guang Wang, Pietro Lio, Ming Li, Guido Montufar How Framelets
Enhance Graph Neural Networks. ICLM 2021
Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido
Montúfar, Pietro Liò, Michael Bronstein
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks. ICLM 2021

 

Publications

Journal articles

  • Nain, Z., Rana, HK., Liò, P., Islam, SMS., Summers, MA. and Moni, MA., 2021. Pathogenetic profiling of COVID-19 and SARS-like viruses. Briefings Bioinform., v. 22
  • Charoenkwan, P., Nantasenamat, C., Hasan, MM., Moni, MA., Lio', P. and Shoombuatong, W., 2021. Ibitter‐fuse: A novel sequence‐based bitter peptide predictor by fusing multi‐view features Int J Mol Sci, v. 22
    Doi: 10.3390/ijms22168958
  • D'Agostino, D., Liò, P., Aldinucci, M. and Merelli, I., 2021. Advantages of using graph databases to explore chromatin conformation capture experiments. BMC Bioinformatics, v. 22
    Doi: http://doi.org/10.1186/s12859-020-03937-0
  • Jamasb, AR., Day, B., Cangea, C., Liò, P. and Blundell, TL., 2021. Deep Learning for Protein-Protein Interaction Site Prediction. Methods Mol Biol, v. 2361
    Doi: http://doi.org/10.1007/978-1-0716-1641-3_16
  • Chen, K., Xu, H., Lei, Y., Lio, P., Li, Y., Guo, H. and Ali Moni, M., 2021. Integration and interplay of machine learning and bioinformatics approach to identify genetic interaction related to ovarian cancer chemoresistance. Brief Bioinform,
    Doi: http://doi.org/10.1093/bib/bbab100
  • Rashed-Al-Mahfuz, M., Moni, MA., Lio', P., Islam, SMS., Berkovsky, S., Khushi, M. and Quinn, JMW., 2021. Deep convolutional neural networks based ECG beats classification to diagnose cardiovascular conditions Biomed Eng Lett, v. 11
    Doi: 10.1007/s13534-021-00185-w
  • Shankar, V., Tibshirani, R. and Zare, RN., 2021. Adversarial generation of gene expression data. Bioinformatics,
    Doi: 10.1093/bioinformatics/btab282
  • Zhu, J., Tan, C., Yang, J., Yang, G. and Lio', P., 2021. Arbitrary Scale Super-Resolution for Medical Images. Int J Neural Syst,
    Doi: http://doi.org/10.1142/S0129065721500374
  • Hwang, J. and Lio, PA., 2021. Topical corticosteroid withdrawal ('steroid addiction'): an update of a systematic review. J Dermatolog Treat,
    Doi: http://doi.org/10.1080/09546634.2021.1882659
  • Azevedo, T., Dimitri, GM., Lió, P. and Gamazon, ER., 2021. Multilayer modelling of the human transcriptome and biological mechanisms of complex diseases and traits. NPJ Syst Biol Appl, v. 7
    Doi: http://doi.org/10.1038/s41540-021-00186-6
  • van Der Schaar, M., Alaa, AM., Floto, A., Gimson, A., Scholtes, S., Wood, A., McKinney, E., Jarrett, D., Lio, P. and Ercole, A., 2021. How artificial intelligence and machine learning can help healthcare systems respond to COVID-19 Machine Learning, v. 110
    Doi: http://doi.org/10.1007/s10994-020-05928-x
  • Weber, JM., Lindenmeyer, CP., Liò, P. and Lapkin, AA., 2021. Teaching sustainability as complex systems approach: a sustainable development goals workshop International Journal of Sustainability in Higher Education, v. 22
    Doi: http://doi.org/10.1108/IJSHE-06-2020-0209
  • Islam, MR., Moni, MA., Islam, MM., Rashed-Al-Mahfuz, M., Islam, MS., Hasan, MK., Hossain, MS., Ahmad, M., Uddin, S., Azad, A., Alyami, SA., Ahad, MAR. and Lio, P., 2021. Emotion Recognition From EEG Signal Focusing on Deep Learning and Shallow Learning Techniques IEEE Access, v. 9
    Doi: 10.1109/ACCESS.2021.3091487
  • Pirazzini, C., Azevedo, T., Baldelli, L., Bartoletti-Stella, A., Calandra-Buonaura, G., Dal Molin, A., Dimitri, GM., Doykov, I., Gómez-Garre, P., Hägg, S., Hällqvist, J., Halsband, C., Heywood, W., Jesús, S., Jylhävä, J., Kwiatkowska, KM., Labrador-Espinosa, MA., Licari, C., Maturo, MG., Mengozzi, G., Meoni, G., Milazzo, M., Periñán-Tocino, MT., Ravaioli, F., Sala, C., Sambati, L., Schade, S., Schreglmann, S., Spasov, S., Tenori, L., Williams, D., Xumerle, L., Zago, E., Bhatia, KP., Capellari, S., Cortelli, P., Garagnani, P., Houlden, H., Liò, P., Luchinat, C., Delledonne, M., Mills, K., Mir, P., Mollenhauer, B., Nardini, C., Pedersen, NL., Provini, F., Strom, S., Trenkwalder, C., Turano, P., Bacalini, MG., Franceschi, C. and PROPAG-AGEING Consortium, , 2021. A geroscience approach for Parkinson's disease: Conceptual framework and design of PROPAG-AGEING project. Mech Ageing Dev, v. 194
    Doi: http://doi.org/10.1016/j.mad.2020.111426
  • Caccuri, F., D'Ursi, P., Uggeri, M., Bugatti, A., Mazzuca, P., Zani, A., Filippini, F., Salmona, M., Ribatti, D., Slevin, M., Orro, A., Lu, W., Liò, P., Gallo, RC. and Caruso, A., 2021. Evolution toward beta common chain receptor usage links the matrix proteins of HIV-1 and its ancestors to human erythropoietin. Proc Natl Acad Sci U S A, v. 118
    Doi: http://doi.org/10.1073/pnas.2021366118
  • Merelli, I., Liò, P., Kotenko, I. and D'Agostino, D., 2020. Latest advances in parallel, distributed, and network-based processing Concurrency and Computation: Practice and Experience, v. 32
    Doi: 10.1002/cpe.5683
  • Spasov, SE. and Liò, P., 2020. Dynamic neural network channel execution for efficient training 30th British Machine Vision Conference 2019, BMVC 2019,
  • Lu, X., Zhang, S., Hui, P. and Lio, P., 2020. Continuous authentication by free-text keystroke based on CNN and RNN Computers and Security, v. 96
    Doi: 10.1016/j.cose.2020.101861
  • Stefano, AD., Scatà, M., Attanasio, B., Corte, AL., Lió, P. and Das, SK., 2020. A Novel Methodology for designing Policies in Mobile Crowdsensing Systems. Pervasive Mob. Comput., v. 67
    Doi: 10.1016/j.pmcj.2020.101230
  • Barbiero, P. and Lió, P., 2020. The computational Patient has diabetes and a COVID
    Doi: http://doi.org/10.1101/2020.06.10.20127183
  • Barbiero, P., Torné, RV. and Lió, P., 2020. Graph representation forecasting of patient’s medical conditions: towards a digital twin Frontiers in Genetics,
  • Scata, M., Di Stefano, A., La Corte, A. and Lio, P., 2020. A Multiplex Social Contagion Dynamics Model to shape and discriminate D2D content dissemination IEEE Transactions on Cognitive Communications and Networking, v. 7
    Doi: 10.1109/TCCN.2020.3027697
  • Lu, X., Zhou, X., Wang, W., Lio, P. and Hui, P., 2020. Domain-oriented topic discovery based on features extraction and topic clustering IEEE Access, v. 8
    Doi: 10.1109/ACCESS.2020.2994516
  • Viñas, R., Azevedo, T., Gamazon, E. and Liò, P., 2020. Gene Expression Imputation with Generative Adversarial Imputation Nets
    Doi: 10.1101/2020.06.09.141689
  • Bardozzo, F., Lió, P. and Tagliaferri, R., 2020. Signal metrics analysis of oscillatory patterns in bacterial multi-omic networks. Bioinformatics, v. 37
    Doi: 10.1093/bioinformatics/btaa966
  • Azevedo, T., Dimitri, GM., Lio, P. and Gamazon, E., 2020. Multilayer modelling and analysis of the human transcriptome
    Doi: http://doi.org/10.1101/2020.05.21.109082
  • Azevedo, T., Campbell, A., Romero-Garcia, R., Passamonti, L., Bethlehem, RAI., Liò, P. and Toschi, N., 2020. A Deep Graph Neural Network Architecture for Modelling Spatio-temporal Dynamics in resting-state functional MRI Data
    Doi: 10.1101/2020.11.08.370288
  • Nain, Z., Rana, HK., Liò, P., Islam, SMS., Summers, MA. and Moni, MA., 2020. Pathogenetic profiling of COVID-19 and SARS-like viruses. Briefings in Bioinformatics,
    Doi: http://doi.org/10.1093/bib/bbaa173
  • Di Stefano, A., Scatá, M., Attanasio, B., La Corte, A., Lió, P. and Das, SK., 2020. A Novel Methodology for designing Policies in Mobile Crowdsensing Systems Pervasive and Mobile Computing, v. 67
    Doi: http://doi.org/10.1016/j.pmcj.2020.101230
  • Barbiero, P., Viñas Torné, R. and Lió, P., 2020. Graph representation forecasting of patient’s medical conditions: towards a digital twin
    Doi: 10.1101/2020.09.19.20197764
  • John, MS., Nagoth, JA., Ramasamy, KP., Ballarini, P., Mozzicafreddo, M., Mancini, A., Telatin, A., Liò, P., Giuli, G., Natalello, A., Miceli, C. and Pucciarelli, S., 2020. Horizontal gene transfer and silver nanoparticles production in a new Marinomonas strain isolated from the Antarctic psychrophilic ciliate Euplotes focardii. Scientific Reports, v. 10
    Doi: http://doi.org/10.1038/s41598-020-66878-x
  • Rollins, CPE., Garrison, JR., Arribas, M., Seyedsalehi, A., Li, Z., Chan, RCK., Yang, J., Wang, D., Liò, P., Yan, C., Yi, Z-H., Cachia, A., Upthegrove, R., Deakin, B., Simons, JS., Murray, GK. and Suckling, J., 2020. Evidence in cortical folding patterns for prenatal predispositions to hallucinations in schizophrenia. Transl Psychiatry, v. 10
    Doi: http://doi.org/10.1038/s41398-020-01075-y
  • Lu, X., Liao, Y., Lio, P. and Pan, H., 2020. An Asynchronous Federated Learning Mechanism for Edge Network Computing Jisuanji Yanjiu yu Fazhan/Computer Research and Development, v. 57
    Doi: 10.7544/issn1000-1239.2020.20190754
  • Ahamad, MM., Aktar, S., Rashed-Al-Mahfuz, M., Uddin, S., Liò, P., Xu, H., Summers, MA., Quinn, JMW. and Moni, MA., 2020. A machine learning model to identify early stage symptoms of SARS-Cov-2 infected patients. Expert Systems with Applications, v. 160
    Doi: http://doi.org/10.1016/j.eswa.2020.113661
  • Lu, X., Wang, X., Lio, P. and Hui, P., 2020. DADIM: A distance adjustment dynamic influence map model Future Generation Computer Systems, v. 112
    Doi: 10.1016/j.future.2020.06.020
  • Cangea, C., Velickovic, P. and Liò, P., 2020. XFlow: Cross-Modal Deep Neural Networks for Audiovisual Classification. IEEE Trans. Neural Networks Learn. Syst., v. 31
    Doi: 10.1109/TNNLS.2019.2945992
  • Tan, C., Zhu, J. and Lio’, P., 2020. Arbitrary scale super-resolution for brain MRI images IFIP Advances in Information and Communication Technology, v. 583 IFIP
    Doi: 10.1007/978-3-030-49161-1_15
  • Kazhdan, D., Dimanov, B., Jamnik, M., Liò, P. and Weller, A., 2020. Now You See Me (CME): Concept-based Model Extraction. CoRR, v. abs/2010.13233
  • Deasy, J., Rocheteau, E., Kohler, K., Stubbs, D., Barbiero, P., Liò, P. and Ercole, A., 2020. Forecasting ultra-early intensive care strain from COVID-19 in England medrxiv,
    Doi: http://doi.org/10.1101/2020.03.19.20039057
  • Müller, TT. and Lio, P., 2020. PECLIDES Neuro: A Personalisable Clinical Decision Support System for Neurological Diseases. Front Artif Intell, v. 3
    Doi: 10.3389/frai.2020.00023
  • Lu, X., Liao, Y., Lio, P. and Hui, P., 2020. Privacy-preserving asynchronous federated learning mechanism for edge network computing IEEE Access, v. 8
    Doi: 10.1109/ACCESS.2020.2978082
  • Rakowski, AG., Veličković, P., Dall'Ara, E. and Liò, P., 2020. ChronoMID-Cross-modal neural networks for 3-D temporal medical imaging data. PLoS One, v. 15
    Doi: http://doi.org/10.1371/journal.pone.0228962
  • Rana, HK., Akhtar, MR., Islam, MB., Ahmed, MB., Lió, P., Huq, F., Quinn, JMW. and Moni, MA., 2020. Machine Learning and Bioinformatics Models to Identify Pathways that Mediate Influences of Welding Fumes on Cancer Progression. Sci Rep, v. 10
    Doi: http://doi.org/10.1038/s41598-020-57916-9
  • Kazhdan, D., Shams, Z. and Lio, P., 2020. MARLeME: A Multi-Agent Reinforcement Learning Model Extraction Library Proceedings of the International Joint Conference on Neural Networks,
    Doi: 10.1109/IJCNN48605.2020.9207564
  • Wang, D., Jamnik, M. and Liò, P., 2020. Abstract Diagrammatic Reasoning with Multiplex Graph Networks. CoRR, v. abs/2006.11197
  • Prokhorov, V., Pilehvar, MT., Kartsaklis, D., Liò, P. and Collier, N., 2019. Unseen word representation by aligning heterogeneous lexical semantic spaces 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019,
  • Di Stefano, A., Scatà, M., Vijayakumar, S., Angione, C., La Corte, A. and Liò, P., 2019. Social dynamics modeling of chrono-nutrition. PLoS Comput Biol, v. 15
    Doi: http://doi.org/10.1371/journal.pcbi.1006714
  • Vignani, R., Liò, P. and Scali, M., 2019. How to integrate wet lab and bioinformatics procedures for wine DNA admixture analysis and compositional profiling: Case studies and perspectives. PLoS One, v. 14
    Doi: http://doi.org/10.1371/journal.pone.0211962
  • Yang, J., Wang, D., Rollins, C., Leming, M., Liò, P., Suckling, J., Murray, G., Garrison, J. and Cachia, A., 2019. Volumetric Segmentation and Characterisation of the Paracingulate Sulcus on MRI Scans
    Doi: http://doi.org/10.1101/859496
  • Smith, HL., Stevens, A., Minogue, B., Sneddon, S., Shaw, L., Wood, L., Adeniyi, T., Xiao, H., Lio, P., Kimber, SJ. and Brison, DR., 2019. Systems based analysis of human embryos and gene networks involved in cell lineage allocation. BMC Genomics, v. 20
    Doi: http://doi.org/10.1186/s12864-019-5558-8
  • Cangea, C., Velickovic, P. and Lio, P., 2019. XFlow: Cross-Modal Deep Neural Networks for Audiovisual Classification. IEEE Trans Neural Netw Learn Syst,
    Doi: http://doi.org/10.1109/TNNLS.2019.2945992
  • Bartoszek, K. and Liò, P., 2019. Modelling trait-dependent speciation with approximate Bayesian computation Acta Physica Polonica B, Proceedings Supplement, v. 12
    Doi: 10.5506/APhysPolBSupp.12.25
  • Pernice, S., Follia, L., Balbo, G., Milanesi, L., Sartini, G., Totis, N., Lió, P., Merelli, I., Cordero, F. and Beccuti, M., 2019. Integrating Petri Nets and Flux Balance Methods in Computational Biology Models: A Methodological and Computational Practice Fundamenta Informaticae, v. 171
    Doi: 10.3233/FI-2020-1888
  • Simidjievski, N., Bodnar, C., Tariq, I., Scherer, P., Andres-Terre, H., Shams, Z., Jamnik, M. and Liò, P., 2019. Variational autoencoders for cancer data integration: design principles and computational practice
    Doi: 10.1101/719542
  • Simidjievski, N., Bodnar, C., Tariq, I., Scherer, P., Andres Terre, H., Shams, Z., Jamnik, M. and Liò, P., 2019. Variational Autoencoders for Cancer Data Integration: Design Principles and Computational Practice. Front Genet, v. 10
    Doi: 10.3389/fgene.2019.01205
  • Akter, T., Shahriare Satu, M., Khan, MI., Ali, MH., Uddin, S., Lio, P., Quinn, JMW. and Moni, MA., 2019. Machine Learning-Based Models for Early Stage Detection of Autism Spectrum Disorders IEEE Access, v. 7
    Doi: 10.1109/ACCESS.2019.2952609
  • Rana, HK., Akhtar, MR., Ahmed, MB., Liò, P., Quinn, JMW., Huq, F. and Moni, MA., 2019. Genetic effects of welding fumes on the progression of neurodegenerative diseases. Neurotoxicology, v. 71
    Doi: http://doi.org/10.1016/j.neuro.2018.12.002
  • Rana, HK., Akhtar, MR., Islam, MB., Ahmed, MB., Liò, P., Quinn, JMW., Huq, F. and Moni, MA., 2019. Genetic effects of welding fumes on the development of respiratory system diseases. Comput Biol Med, v. 108
    Doi: http://doi.org/10.1016/j.compbiomed.2019.04.004
  • Tangherloni, A., Spolaor, S., Rundo, L., Nobile, MS., Cazzaniga, P., Mauri, G., Liò, P., Merelli, I. and Besozzi, D., 2019. GenHap: a novel computational method based on genetic algorithms for haplotype assembly. BMC Bioinform., v. 20-S
    Doi: 10.1186/s12859-019-2691-y
  • Parmar, V. and Lió, P., 2019. Multi-omic network regression: Methodology, tool and case study Studies in Computational Intelligence, v. 813
    Doi: 10.1007/978-3-030-05414-4_49
  • Xiaofeng, L., Fangshuo, J., Xiao, Z., Shengwei, Y., Jing, S. and Lio, P., 2019. ASSCA: API sequence and statistics features combined architecture for malware detection Computer Networks, v. 157
    Doi: 10.1016/j.comnet.2019.04.007
  • Haider, S., Yao, CQ., Sabine, VS., Grzadkowski, M., Stimper, V., Starmans, MHW., Wang, J., Nguyen, F., Moon, NC., Lin, X., Drake, C., Crozier, CA., Brookes, CL., van de Velde, CJH., Hasenburg, A., Kieback, DG., Markopoulos, CJ., Dirix, LY., Seynaeve, C., Rea, DW., Kasprzyk, A., Lambin, P., Lio', P., Bartlett, JMS. and Boutros, PC., 2018. Pathway-based subnetworks enable cross-disease biomarker discovery. Nat Commun, v. 9
    Doi: http://doi.org/10.1038/s41467-018-07021-3
  • Karazija, L., Velickovic, P. and Liò, P., 2018. Automatic Inference of Cross-modal Connection Topologies for X-CNNs. CoRR, v. abs/1805.00987
  • Del Prete, E., Facchiano, A. and Liò, P., 2018. Bioinformatics methodologies for coeliac disease and its comorbidities. Brief Bioinform,
    Doi: http://doi.org/10.1093/bib/bby109
  • He, P., Nakano, T., Mao, Y., Lio, P., Liu, Q. and Yang, K., 2018. Stochastic Channel Switching of Frequency-Encoded Signals in Molecular Communication Networks IEEE Communications Letters, v. 22
    Doi: 10.1109/LCOMM.2017.2768537
  • Dimitri, GM., Agrawal, S., Young, A., Donnelly, J., Liu, X., Smielewski, P., Hutchinson, P., Czosnyka, M., Lio, P. and Haubrich, C., 2018. Simultaneous Transients of Intracranial Pressure and Heart Rate in Traumatic Brain Injury: Methods of Analysis. Acta Neurochirurgica: Supplementum, v. 126
    Doi: http://doi.org/10.1007/978-3-319-65798-1_31
  • Tordini, F., Aldinucci, M., Viviani, P., Merelli, I. and Liò, P., 2018. Scientific Workflows on Clouds with Heterogeneous and Preemptible Instances Advances in Parallel Computing, v. 32
    Doi: 10.3233/978-1-61499-843-3-605
  • Iuliano, A., Occhipinti, A., Angelini, C., De Feis, I. and Liò, P., 2018. Combining Pathway Identification and Breast Cancer Survival Prediction via Screening-Network Methods. Front Genet, v. 9
    Doi: http://doi.org/10.3389/fgene.2018.00206
  • Mancini, A., Eyassu, F., Conway, M., Occhipinti, A., Liò, P., Angione, C. and Pucciarelli, S., 2018. CiliateGEM: an open-project and a tool for predictions of ciliate metabolic variations and experimental condition design. BMC Bioinformatics, v. 19
    Doi: http://doi.org/10.1186/s12859-018-2422-9
  • Scatà, M., Di Stefano, A., La Corte, A. and Liò, P., 2018. Quantifying the propagation of distress and mental disorders in social networks. Sci Rep, v. 8
    Doi: http://doi.org/10.1038/s41598-018-23260-2
  • Bardozzo, F., Lió, P. and Tagliaferri, R., 2018. A study on multi-omic oscillations in Escherichia coli metabolic networks. BMC Bioinformatics, v. 19
    Doi: http://doi.org/10.1186/s12859-018-2175-5
  • Xiao, H., Bartoszek, K. and Lio', P., 2018. Multi-omic analysis of signalling factors in inflammatory comorbidities. BMC Bioinformatics, v. 19
    Doi: http://doi.org/10.1186/s12859-018-2413-x
  • Saggese, I., Bona, E., Conway, M., Favero, F., Ladetto, M., Liò, P., Manzini, G. and Mignone, F., 2018. 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, v. 19
    Doi: http://doi.org/10.1186/s12859-018-2174-6
  • Bartocci, E., Lio, P. and Paoletti, N., 2018. Guest Editors' Introduction to the Special Section on the 14th International Conference on Computational Methods in Systems Biology (CMSB 2016) IEEE/ACM Transactions on Computational Biology and Bioinformatics, v. 15
    Doi: http://doi.org/10.1109/TCBB.2018.2816979
  • Velickovic, P., Karazija, L., Lane, ND., Bhattacharya, S., Liberis, E., Lio, P., Chieh, A., Bellahsen, O. and Vegreville, M., 2018. Cross-modal recurrent models forweight objective prediction from multimodal time-series data ACM International Conference Proceeding Series,
    Doi: 10.1145/3240925.3240937
  • He, P., Nakano, T., Mao, Y., Liò, P., Liu, Q. and Yang, K., 2018. Stochastic Channel Switching of Frequency-Encoded Signals in Molecular Communication Networks. IEEE Commun. Lett., v. 22
    Doi: 10.1109/LCOMM.2017.2768537
  • Felicetti, L., Femminella, M., Reali, G. and Liò, P., 2018. Applications of molecular communications to medicine: a survey. CoRR, v. abs/1808.04242
  • Veličković, P., Casanova, A., Liò, P., Cucurull, G., Romero, A. and Bengio, Y., 2018. Graph attention networks 6th International Conference on Learning Representations, ICLR 2018 - Conference Track Proceedings,
  • Liberis, E., Velickovic, P., Sormanni, P., Vendruscolo, M. and Liò, P., 2018. Parapred: antibody paratope prediction using convolutional and recurrent neural networks. Bioinformatics, v. 34
    Doi: http://doi.org/10.1093/bioinformatics/bty305
  • Vijayakumar, S., Conway, M., Lió, P. and Angione, C., 2018. Seeing the wood for the trees: a forest of methods for optimization and omic-network integration in metabolic modelling. Briefings in Bioinformatics, v. 19
    Doi: http://doi.org/10.1093/bib/bbx053
  • Karazija, L., Veličković, P. and Liò, P., 2018. Automatic inference of cross-modal connection topologies for X-CNNs Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 10878 LNCS
    Doi: 10.1007/978-3-319-92537-0_7
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  • Sheehan, C., Day, B. and Liò, P., Introducing Curvature to the Label Space
  • Day, B., Cangea, C., Jamasb, AR. and Liò, P., Message Passing Neural Processes
  • Christensen, CN., Ward, E., Lio, P. and Kaminski, C., ML-SIM: Universal reconstruction of structured illumination microscopy images using transfer learning Biomedical Optics Express,
    Doi: http://doi.org/10.1364/boe.414680
  • Fanfani, V., Vinas Torne, R., Lio', P. and Stracquadanio, G., Discovering cancer driver genes and pathways using stochastic block model graph neural networks
    Doi: http://doi.org/10.1101/2021.06.29.450342
  • Peychev, M., Veličković, P. and Liò, P., Quantifying the Effects of Enforcing Disentanglement on Variational Autoencoders
  • Ciravegna, G., Barbiero, P., Giannini, F., Gori, M., Lió, P., Maggini, M. and Melacci, S., Logic Explained Networks
  • Maria, ED., Despeyroux, J., Felty, A., Liò, P., Olarte, C. and Bahrami, A., Computational Logic for Biomedicine and Neurosciences
  • Cangea, C., Veličković, P., Jovanović, N., Kipf, T. and Liò, P., Towards Sparse Hierarchical Graph Classifiers
  • Zhao, Y., Wang, D., Bates, D., Mullins, R., Jamnik, M. and Lio, P., Learned Low Precision Graph Neural Networks
  • Conference proceedings

  • Zubic, N. and Liò, P., 2021. An Effective Loss Function for Generating 3D Models from Single 2D Image Without Rendering. AIAI, v. 627
  • Bodnar, C., Frasca, F., Wang, Y., Otter, N., Montúfar, GF., Lió, P. and Bronstein, MM., 2021. Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks. ICML, v. 139
  • Zheng, X., Zhou, B., Gao, J., Wang, Y., Lió, P., Li, M. and Montúfar, G., 2021. How Framelets Enhance Graph Neural Networks. ICML, v. 139
  • Beaini, D., Passaro, S., Létourneau, V., Hamilton, WL., Corso, G. and Lió, P., 2021. Directional Graph Networks. ICML, v. 139
  • Rocheteau, E., Liò, P. and Hyland, SL., 2021. Temporal pointwise convolutional networks for length of stay prediction in the intensive care unit. CHIL,
  • Norcliffe, A., Bodnar, C., Day, B., Moss, J. and Liò, P., 2021. Neural ODE Processes. ICLR,
  • Dimitri, GM., Beqiri, E., Placek, MM., Czosnyka, M., Ercole, A., Smielewski, P. and Lio, P., 2020. Introducing brain-heart crosstalks information in clinical decision support systems for TBI patients, through ICM+ 2020 11th Conference of the European Study Group on Cardiovascular Oscillations: Computation and Modelling in Physiology: New Challenges and Opportunities, ESGCO 2020,
    Doi: 10.1109/ESGCO49734.2020.9158050
  • Di Stefano, A., Maesa, DDF., Das, SK. and Liò, P., 2020. Resolution of Blockchain Conflicts through Heuristics-based Game Theory and Multilayer Network Modeling. ICDCN 2020: Proceedings of the 21st International Conference on Distributed Computing and Networking,
    Doi: http://doi.org/10.1145/3369740.3372914
  • Dimitri, GM., Spasov, S., Duggento, A., Passamonti, L., Lio, P. and Toschi, N., 2020. Unsupervised stratification in neuroimaging through deep latent embeddings. Annu Int Conf IEEE Eng Med Biol Soc, v. 2020
    Doi: http://doi.org/10.1109/EMBC44109.2020.9175810
  • Azevedo, T., Passamonti, L., Lio, P. and Toschi, N., 2020. A deep spatiotemporal graph learning architecture for brain connectivity analysis. Annu Int Conf IEEE Eng Med Biol Soc, v. 2020
    Doi: http://doi.org/10.1109/EMBC44109.2020.9175360
  • Yeghikyan, G., Opolka, FL., Nanni, M., Lepri, B. and Lio, P., 2020. Learning Mobility Flows from Urban Features with Spatial Interaction Models and Neural Networks**To appear in the Proceedings of 2020 IEEE International Conference on Smart Computing (SMARTCOMP 2020) Proceedings - 2020 IEEE International Conference on Smart Computing, SMARTCOMP 2020,
    Doi: 10.1109/SMARTCOMP50058.2020.00028
  • Norcliffe, A., Bodnar, C., Day, B., Simidjievski, N. and Lió, P., 2020. On Second Order Behaviour in Augmented Neural ODEs. NeurIPS,
  • Deasy, J., Simidjievski, N. and Lió, P., 2020. Constraining Variational Inference with Geometric Jensen-Shannon Divergence. NeurIPS,
  • Corso, G., Cavalleri, L., Beaini, D., Liò, P. and Velickovic, P., 2020. Principal Neighbourhood Aggregation for Graph Nets. NeurIPS,
  • Wang, D., Jamnik, M. and Lio, P., 2020. Abstract Diagrammatic Reasoning with Multiplex Graph Networks
  • Ma, Z., Xuan, J., Wang, YG., Li, M. and Liò, P., 2020. Path Integral Based Convolution and Pooling for Graph Neural Networks. NeurIPS,
  • Kusztos, R., Dimitri, GM. and Lió, P., 2020. Neural Models for Brain Networks Connectivity Analysis Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 11925 LNBI
    Doi: 10.1007/978-3-030-34585-3_19
  • D’Agostino, D., Liò, P., Aldinucci, M. and Merelli, I., 2020. NeoHiC: A web application for the analysis of Hi-C data Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 12313 LNBI
    Doi: 10.1007/978-3-030-63061-4_10
  • Bodnar, C., Day, B. and Lió, P., 2020. Proximal Distilled Evolutionary Reinforcement Learning. AAAI,
  • Zhu, J., Tan, C., Yang, J., Yang, G. and Lio', P., 2020. Arbitrary Scale Super-Resolution for Brain MRI Images. International Journal of Neural Systems,
    Doi: 10.1142/S0129065721500374
  • Cangea, C., Belilovsky, E., Liò, P. and Courville, AC., 2019. VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering. ViGIL@NeurIPS,
  • Tangherloni, A., Rundo, L., Spolaor, S., Nobile, MS., Merelli, I., Besozzi, D., Mauri, G., Cazzaniga, P. and Liò, P., 2019. High performance computing for haplotyping: Models and platforms Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 11339 LNCS
    Doi: 10.1007/978-3-030-10549-5_51
  • Zhu, J., Yang, G. and Liò, P., 2019. How Can We Make Gan Perform Better in Single Medical Image Super-Resolution? A Lesion Focused Multi-Scale Approach. ISBI,
  • Despeyroux, J., Felty, A., Liò, P. and Olarte, C., 2019. A Logical Framework for Modelling Breast Cancer Progression Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 11415 LNCS
    Doi: 10.1007/978-3-030-19432-1_8
  • Serra, A., Guida, MD., Lió, P. and Tagliaferri, R., 2019. Hierarchical block matrix approach for multi-view clustering Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 10834 LNBI
    Doi: 10.1007/978-3-030-14160-8_19
  • Zhu, J., Yang, G. and Lió, P., 2019. Lesion focused super-resolution. Medical Imaging: Image Processing, v. 10949
  • Satu, MS., Chandra Howlader, K., Niamat Ullah Akhund, TM., Quinn, JMW., Lio, P. and Moni, MA., 2019. Comorbidity effects of mitochondrial dysfunction to the progression of neurological disorders: Insights from a systems biomedicine perspective 2019 22nd International Conference on Computer and Information Technology, ICCIT 2019,
    Doi: 10.1109/ICCIT48885.2019.9038388
  • Di Stefano, A., Scatà, M., La Corte, A., Das, SK. and Liò, P., 2019. Improving QoE in multi-layer social sensing: A cognitive architecture and game theoretic model SocialSense'19 Proceedings of the Fourth International Workshop on Social Sensing,
    Doi: http://doi.org/10.1145/3313294.3313384
  • Spasov, SE. and Liò, P., 2019. Dynamic Neural Network Channel Execution for Efficient Training. BMVC,
  • Veličković, P., Fedus, W., Hamilton, WL., Bengio, Y., Liò, P. and Devon Hjelm, R., 2019. Deep graph infomax 7th International Conference on Learning Representations, ICLR 2019,
  • Velickovic, P., Karazija, L., Lane, ND., Bhattacharya, S., Liberis, E., Liò, P., Chieh, A., Bellahsen, O. and Vegreville, M., 2018. Cross-modal Recurrent Models for Weight Objective Prediction from Multimodal Time-series Data. PervasiveHealth,
  • Spasov, SE., Passamonti, L., Duggento, A., Lio, P. and Toschi, N., 2018. A Multi-modal Convolutional Neural Network Framework for the Prediction of Alzheimer's Disease. Annu Int Conf IEEE Eng Med Biol Soc, v. 2018
    Doi: http://doi.org/10.1109/EMBC.2018.8512468
  • 2018. 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing, PDP 2018, Cambridge, United Kingdom, March 21-23, 2018 PDP,
  • Merelli, I., Lio, P. and Kotenko, I., 2018. Message from General Chairs Proceedings - 26th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2018,
    Doi: http://doi.org/10.1109/PDP2018.2018.00005
  • Merelli, I., Lio, P. and Kotenko, I., 2018. Message from Organizing Chairs Proceedings - 26th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2018,
    Doi: http://doi.org/10.1109/PDP2018.2018.00006
  • Lu, X., Liang, C., Zhang, S., Lio, P. and Jing, S., 2018. Terminal sensitive data protection by adjusting access time bidirectionally and automatically Proceedings - International Conference on Computer Communications and Networks, ICCCN, v. 2018-July
    Doi: 10.1109/ICCCN.2018.8487465
  • Wang, D., Zhang, R., Zhu, J., Teng, Z., Huang, Y., Spiga, F., Hong-Fei Du, M., Gillard, JH., Lu, Q. and Liò, P., 2018. Neural network fusion: a novel CT-MR Aortic Aneurysm image segmentation method. Proc SPIE Int Soc Opt Eng, v. 10574
    Doi: http://doi.org/10.1117/12.2293371
  • Bica, I., Veličković, P., Xiao, H. and Liò, P., 2018. Multi-omics data integration using cross-modal neural networks ESANN 2018 - Proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning,
  • Mathur, A., Zhang, T., Bhattacharya, S., Velickovic, P., Joffe, L., Lane, ND., Kawsar, F. and Liò, P., 2018. Using deep data augmentation training to address software and hardware heterogeneities in wearable and smartphone sensing devices. IPSN '18 Proceedings of the 17th ACM/IEEE International Conference on Information Processing in Sensor Networks,
    Doi: http://doi.org/10.1109/IPSN.2018.00048
  • Veličković, P., Casanova, A., Liò, P., Cucurull, G., Romero, A. and Bengio, Y., 2018. Graph attention networks 6th International Conference on Learning Representations, ICLR 2018 - Conference Track Proceedings,
  • Brouwer, T. and Lio, P., 2017. Bayesian Hybrid Matrix Factorisation for Data Integration Proceedings of Machine Learning Research, v. 54
  • Brouwer, T., Frellsen, J. and Liò, P., 2017. Comparative Study of Inference Methods for Bayesian Nonnegative Matrix Factorisation. ECML/PKDD (1), v. 10534
    Doi: http://doi.org/10.1007/978-3-319-71249-9_31)
  • Heffernan, K., Liò, P. and Teufel, S., 2017. Multilayer data and document stratification for comorbidity analysis Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 10477 LNBI
    Doi: 10.1007/978-3-319-67834-4_17
  • Felicetti, L., Femminella, M., Ivanov, T., Lio, P. and Reali, G., 2017. A big-data layered architecture for analyzing molecular communications systems in blood vessels Proceedings of the 4th ACM International Conference on Nanoscale Computing and Communication, NanoCom 2017,
    Doi: 10.1145/3109453.3109468
  • Pratanwanich, N., Lió, P. and Stegle, O., 2016. Warped matrix factorisation for multi-view data integration Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 9852 LNAI
    Doi: 10.1007/978-3-319-46227-1_49
  • Alarcon, E., Cid-Fuentes, RG., Davy, A., Felicetti, L., Femminella, M., Lio, P., Reali, G. and Solé-Pareta, J., 2016. MolComML: The molecular communication markup language Proceedings of the 3rd ACM International Conference on Nanoscale Computing and Communication, ACM NANOCOM 2016,
    Doi: 10.1145/2967446.2967460
  • 2016. Computational Methods in Systems Biology - 14th International Conference, CMSB 2016, Cambridge, UK, September 21-23, 2016, Proceedings CMSB, v. 9859
  • Moni, M. and Lio, P., 2016. Infectome, diseasome and comorbidities of Zika infection INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES, v. 53
    Doi: http://doi.org/10.1016/j.ijid.2016.11.040
  • Lu, X. and Lio, P., 2016. Privacy Information Security Classification and Comparison between the Westerner and Chinese Proceedings - 2015 International Conference on Identification, Information, and Knowledge in the Internet of Things, IIKI 2015,
    Doi: 10.1109/IIKI.2015.10
  • He, P., Mao, Y., Liu, Q., Liò, P. and Yang, K., 2016. Channel modelling of molecular communications across blood vessels and nerves 2016 IEEE International Conference on Communications, ICC 2016,
    Doi: http://doi.org/10.1109/ICC.2016.7510860
  • Velickovic, P., Wang, D., Lane, ND. and Liò, P., 2016. X-CNN: Cross-modal convolutional neural networks for sparse datasets. SSCI,
  • Angione, C., Liò, P., Pucciarelli, S., Can, B., Conway, M., Lotti, M., Bokhari, H., Mancini, A., Sezerman, U. and Telatin, A., 2016. Bioinformatics challenges and potentialities in studying extreme environments Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 9874 LNCS
    Doi: 10.1007/978-3-319-44332-4_16
  • Tordini, F., Merelli, I., Liò, P., Milanesi, L. and Aldinucci, M., 2016. NuchaRT: Embedding high-level parallel computing in R for augmented Hi-C data analysis Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 9874 LNCS
    Doi: 10.1007/978-3-319-44332-4_20
  • Boutorh, A., Pratanwanich, N., Guessoum, A. and Liò, P., 2015. Drug repurposing by optimizing mining of genes target association Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 8623
    Doi: 10.1007/978-3-319-24462-4_18
  • Di Serio, C., Liò, P., Nonis, A. and Tagliaferri, R., 2015. Computational intelligence methods for bioinformatics and biostatistics: 11th international meeting, CIBB 2014 Cambridge, UK, june 26–28, 2014 revised selected papers Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 8623
  • Pratanwanich, N. and Lio, P., 2015. Who wrote this? Textual modeling with authorship attribution in big data IEEE International Conference on Data Mining Workshops, ICDMW, v. 2015-January
    Doi: 10.1109/ICDMW.2014.140
  • Bardozzo, F., Lió, P. and Tagliaferri, R., 2015. Multi omic oscillations in bacterial pathways Proceedings of the International Joint Conference on Neural Networks, v. 2015-September
    Doi: 10.1109/IJCNN.2015.7280853
  • Tordini, F., Drocco, M., Merelli, I., Milanesi, L., Liò, P. and Aldinucci, M., 2015. NuChart-II: A graph-based approach for analysis and interpretation of Hi-C data Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 8623
    Doi: 10.1007/978-3-319-24462-4_25
  • Hamey, FK., Shavit, Y., Maciulyte, V., Town, C., Liò, P. and Tosi, S., 2015. Automated detection of fluorescent probes in molecular imaging Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 8623
    Doi: 10.1007/978-3-319-24462-4_6
  • Iuliano, A., Occhipinti, A., Angelini, C., De Feis, I. and Lió, P., 2015. Applications of network-based survival analysis methods for pathways detection in cancer Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 8623
    Doi: 10.1007/978-3-319-24462-4_7
  • Korhonen, A., Guo, Y., Baker, S., Yetisgen-Yildiz, M., Stenius, U., Narita, M. and Liò, P., 2015. Improving literature-based discovery with advanced text mining Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 8623
    Doi: 10.1007/978-3-319-24462-4_8
  • Tordini, F., Drocco, M., Misale, C., Milanesi, L., Lió, P., Merelli, I. and Aldinucci, M., 2015. Parallel exploration of the nuclear Chromosome Conformation with NuChart-II Proceedings - 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2015,
    Doi: 10.1109/PDP.2015.104
  • Lu, X., Lio, P. and Hui, P., 2015. A content dissemination model for mobile internet to minimize load on cellular network Electronics, Communications and Networks IV - Proceedings of the 4th International Conference on Electronics, Communications and Networks, CECNet2014,
    Doi: 10.1201/b18592-54
  • Tordini, F., Drocco, M., Misale, C., Milanesi, L., Lio, P., Merelli, I. and Aldinucci, M., 2015. Parallel Exploration of the Nuclear Chromosome Conformation with NuChart-II 23RD EUROMICRO INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED, AND NETWORK-BASED PROCESSING (PDP 2015),
    Doi: http://doi.org/10.1109/PDP.2015.104
  • Felicetti, L., Femminella, M., Reali, G. and Liò, P., 2014. Endovascular mobile sensor network for detecting circulating tumoral cells BODYNETS 2014 - 9th International Conference on Body Area Networks,
    Doi: 10.4108/icst.bodynets.2014.256917
  • Bartoszek, K. and Lio, P., 2014. A novel algorithm to reconstruct phylogenies using gene sequences and expression data
  • Lió, P., 2014. Computing longevity: Insights from controls Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 8738 LNBI
    Doi: http://doi.org/10.1007/978-3-319-10398-3_4
  • Lu, X., Lio, P., Hui, P. and Qu, Z., 2014. Nodes density adaptive opportunistic forwarding protocol for intermittently connected networks Proceedings - 2014 International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2014,
    Doi: 10.1109/IIKI.2014.67
  • 2013. Proceedings of the Twelfth European Conference on the Synthesis and Simulation of Living Systems: Advances in Artificial Life, ECAL 2013, Sicily, Italy, September 2-6, 2013 ECAL,
  • Bansal, A., Azad, S. and Lio, P., 2013. Malaria Incidence Forecasting and Its Implication to Intervention Proceedings of the European Conference on Complex Systems 2012,
  • Lio, P., Iacovella, L., Bianchi, L. and Nguyen, V., 2013. Information Filtering and Learning: From Heuristics to Social Eudaimonia Proceedings of the European Conference on Complex Systems 2012,
  • Angione, C., Carapezza, G., Costanza, J., Lio, P. and Nicosia, G., 2013. The Role of the Genome in the Evolution of the Complexity of Metabolic Machines Proceedings of the European Conference on Complex Systems 2012,
  • Bianchi, L., Fernandes, P. and Lio, P., 2013. Improving collective awareness and education about the privacy and ethical issues connected with the genome technologies The Future of Education, Conference Proceedings 2013,
  • Liò, P., 2013. Methodologies for Systems Medicine: Time to Join the Forces of Bioengineering and Bioinformatics. BIOINFORMATICS,
  • Pratanwanich, N. and Lio, P., 2013. Bayesian Inference for Learning Between-Pathway Network: A New Tool for Studying Drug-Disease Interactions HUMAN HEREDITY, v. 76
  • Kim, H., Khoo, WM. and Lio, P., 2012. Polymorphic Attacks against Sequence-based Software Birthmarks
  • 2012. Artificial Immune Systems - 11th International Conference, ICARIS 2012, Taormina, Italy, August 28-31, 2012. Proceedings ICARIS, v. 7597
  • Angione, C., Carapezza, G., Costanza, J., Liò, P. and Nicosia, G., 2012. Computing with Metabolic Machines. Turing-100, v. 10
  • 2011. Artificial Immune Systems - 10th International Conference, ICARIS 2011, Cambridge, UK, July 18-21, 2011. Proceedings ICARIS, v. 6825
  • Lio, P., Emanuela Merelli, and Nicola Paoletti, NP., 2011. Multiple verification in computational modeling of bone pathologies EPTCS, v. 67
  • Merelli, E., Paoletti, N. and Lio, P., 2011. Methodological Bridges for Multi-Level Systems Procedia Computer Science, v. 7
  • Ostilli, M., Yoneki, E., Leung, IXY., Mendes, JFF., Lio, P. and Crowcroft, J., 2010. Statistical mechanics of rumour spreading in network communities ICCS 2010 - INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, PROCEEDINGS, v. 1
    Doi: 10.1016/j.procs.2010.04.262
  • Chan, TM., Leung, KS., Lee, KH. and Lio, P., 2010. Generic Spaced DNA Motif Discovery Using Genetic Algorithm 2010 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC),
  • Kitchovitch, S. and Lio, P., 2010. Risk perception and disease spread on social networks ICCS 2010 - INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, PROCEEDINGS, v. 1
    Doi: http://doi.org/10.1016/j.procs.2010.04.264
  • Guazzini, A., Lio, P., Bagnoli, F., Passarella, A. and Conti, M., 2010. Cognitive network dynamics in chatlines ICCS 2010 - INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, PROCEEDINGS, v. 1
    Doi: http://doi.org/10.1016/j.procs.2010.04.265
  • Papini, A., Nicosia, G., Stracquadanio, G., Lio, P. and Umeton, R., 2010. Key Enzymes for the Optimization of CO2 Uptake and Nitrogen Consumption in the C-3 Photosynthetic Carbon Metabolism JOURNAL OF BIOTECHNOLOGY, v. 150
    Doi: http://doi.org/10.1016/j.jbiotec.2010.09.846
  • Papini, A., Mosti, S., Lio, P. and Haider, S., 2010. BIOLIP, a biotechnology-oriented database of oil content in plants, algae, fungi and cyanobacteria JOURNAL OF BIOTECHNOLOGY, v. 150
    Doi: http://doi.org/10.1016/j.jbiotec.2010.09.012
  • Bartoszek, K., Lio, P. and Sorathiya, A., 2010. INFLUENZA DIFFERENTIATION AND EVOLUTION SUMMER SOLSTICE 2009 INTERNATIONAL CONFERENCE ON DISCRETE MODELS OF COMPLEX SYSTEMS, v. 3
  • Aldinucci, M., Bracciali, A., Liò, P., Sorathiya, A. and Torquati, M., 2010. StochKit-FF: Efficient Systems Biology on Multicore Architectures. Euro-Par Workshops, v. 6586
  • Xie, SK., Lio, P. and Lawniczak, AT., 2009. A Case Study of ICA with Multi-scale PCA of Simulated Traffic Data ARTIFICIAL NEURAL NETWORKS - ICANN 2009, PT II, v. 5769
  • Giampaolo Bella, GB. and Lio, P., 2009. Analysing the microRNA-17-92/Myc/E2F/RB Compound Toggle Switch by Theorem Proving Proc. of the 9th Workshop on Network Tools and Applications in Biology (Nettab’09), v. Liberodiscrivere (2009)
  • Nguyen, VA. and Lio, P., 2009. Measuring similarity between gene expression profiles: a Bayesian approach BMC GENOMICS, v. 10
    Doi: http://doi.org/10.1186/1471-2164-10-S3-S14
  • Lu, Y-E., Roberts, SGB., Cheng, TMK., Dunbar, R., Liò, P. and Crowcroft, J., 2009. On optimising personal network size to manage information flow. CIKM-CNIKM,
  • Hui, P., Xu, K., Li, VOK., Crowcroft, J., Latora, V. and Lio, P., 2009. Selfishness, Altruism and Message Spreading in Mobile Social Networks IEEE INFOCOM 2009 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS,
  • Lu, Y-E., Roberts, SGB., Liò, P., Dunbar, R. and Crowcroft, J., 2009. Size Matters: Variation in Personal Network Size, Personality and Effect on Information Transmission. CSE (4),
    Doi: 10.1109/CSE.2009.179
  • Xie, SK., Lio, P. and Lawniczak, AT., 2009. A Comparative Study of Noise Effect on Wavelet Based De-noising Methods IEEE TIC-STH 09: 2009 IEEE TORONTO INTERNATIONAL CONFERENCE: SCIENCE AND TECHNOLOGY FOR HUMANITY,
  • Xu, K., Hui, P., Li, VOK., Crowcroft, J., Latora, V. and Lio, P., 2009. Impact of Altruism on Opportunistic Communications 2009 FIRST INTERNATIONAL CONFERENCE ON UBIQUITOUS AND FUTURE NETWORKS,
  • Kitchovitch, S., Leung, I., Song, YD. and Lio, P., 2009. Using Mutual Information and Models of Evolution for improved pattern detection 2009 INTERNATIONAL JOINT CONFERENCE ON BIOINFORMATICS, SYSTEMS BIOLOGY AND INTELLIGENT COMPUTING, PROCEEDINGS,
    Doi: http://doi.org/10.1109/IJCBS.2009.77
  • Kitchovitch, S., Song, YD., van der Wath, R. and Lio, P., 2009. Substitution Matrices and Mutual Information Approaches to Modeling Evolution LEARNING AND INTELLIGENT OPTIMIZATION, v. 5851
  • Sorathiya, A., Jucikas, T., Piecewicz, S., Sengupta, S. and Lio, P., 2009. Searching for Glycomics Role in Stem Cell Development COMPUTATIONAL INTELLIGENCE METHODS FOR BIOINFORMATICS AND BIOSTATISTICS, v. 5488
  • Guazzini, A., Lio, P., Passarella, A. and Conti, M., 2009. Information Processing and Timing Mechanisms in Vision ARTIFICIAL NEURAL NETWORKS - ICANN 2009, PT I, v. 5768
  • Bella, G. and Lio, P., 2009. Formal Analysis of the Genetic Toggle COMPUTATIONAL METHODS IN SYSTEMS BIOLOGY, PROCEEDINGS, v. 5688
  • Sorathiyar, A., Lio, P. and Sguanci, L., 2009. Mathematical Model of HIV Superinfection and Comparative Drug Therapy ARTIFICIAL IMMUNE SYSTEMS, PROCEEDINGS, v. 5666
  • Lee, U., Magistretti, E., Gerla, M., Bellavista, P., Lio, P. and Lee, KW., 2008. Bio-Inspired Multi-agent Collaboration for Urban Monitoring Applications BIO-INSPIRED COMPUTING AND COMMUNICATION, v. 5151
  • van der Wath, RC. and Lio, P., 2008. A Stochastic Multi-agent Model of Stem Cell Proliferation CELLULAR AUTOMATA, PROCEEDINGS, v. 5191
  • Kershenbaum, A., Pappas, V., Lee, KW., Lio, P., Sadler, B. and Verma, D., 2008. A biologically-inspired MANET architecture - art. no. 698106 DEFENSE TRANSFORMATION AND NET-CENTRIC SYSTEMS 2008, v. 6981
  • Koukolikova-Nicola, Z., Lio, P. and Bagnoli, F., 2008. Inference on missing values in genetic networks using high-throughput data EVOLUTIONARY COMPUTATION, MACHINE LEARNING AND DATA MINING IN BIOINFORMATICS, PROCEEDINGS, v. 4973
  • Angelini, C., Cutillo, L., De Feis, I., Lio, P. and van der Wath, R., 2008. Combining experimental evidences from replicates and nearby species data for annotating novel genomes COLLECTIVE DYNAMICS: TOPICS ON COMPETITION AND COOPERATION IN THE BIOSCIENCES, v. 1028
  • Leung, IXY., Gibbs, G., Bagnoli, F., Sorathiya, A. and Lio, P., 2008. Contact Network Modeling of Flu Epidemics CELLULAR AUTOMATA, PROCEEDINGS, v. 5191
  • Lio, P., Angelini, C., DeFeis, I., Nguyen, V., Cutillo, L. and va der Wath, R., 2008. Statistical issues for combining replicates and nearby species data and different omics Proceedings The Art and Science of Statistical Bioinformatics The 27th Leeds Annual Statistical Research Workshop 15th - 17th July 2008,
  • Lu, XF., Chen, YC., Leung, I., Xiong, Z. and Lio, P., 2008. A novel mobility model from a heterogeneous military MANET trace AD-HOC, MOBILE AND WIRELESS NETWORKS, PROCEEDINGS, v. 5198
  • van der Wath, RC., van der Wath, E., Carapelli, A., Nardi, F., Frati, F., Milanesi, L. and Lio, P., 2008. Bayesian phylogeny on grid BIOINFORMATICS RESEARCH AND DEVELOPMENT, PROCEEDINGS, v. 13
  • Xie, SK., Lawniczak, AT. and Lio, P., 2008. Parametric & non-parametric analysis of mean treatment effects of number of packets in transit in data network model 2008 CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING, VOLS 1-4,
  • 2008. Bio-Inspired Computing and Communication, First Workshop on Bio-Inspired Design of Networks, BIOWIRE 2007, Cambridge, UK, April 2-5, 2007, Revised Selected Papers BIOWIRE, v. 5151
  • Lu, XF., Wicker, F., Lio', P. and Towsley, D., 2008. Security Estimation Model with Directional Antennas 2008 IEEE MILITARY COMMUNICATIONS CONFERENCE: MILCOM 2008, VOLS 1-7,
  • Allen, SM., Conti, M., Crowcroft, J., Dunbar, R., Liò, P., Mendes, JF., Molva, R., Passarella, A., Stavrakakis, I. and Whitaker, RM., 2008. Social Networking for Pervasive Adaptation. SASO Workshops,
    Doi: 10.1109/SASOW.2008.34
  • Schwarz, E., Leweke, FM., Bahn, S. and Lio, P., 2008. Combining molecular and physiological data of complex disorders BIOINFORMATICS RESEARCH AND DEVELOPMENT, PROCEEDINGS, v. 13
  • Lu, YE., Lio, P. and Hand, S., 2008. Beta Random Projection BIO-INSPIRED COMPUTING AND COMMUNICATION, v. 5151
  • Allen, SM., Conti, M., Crowcroft, J., Dunbar, R., Lio, P., Mendes, JF., Molva, R., Passarella, A., Stavrakakis, I. and Whitaker, RM., 2008. Social Networking for Pervasive Adaptation SASOW 2008: SECOND IEEE INTERNATIONAL CONFERENCE ON SELF-ADAPTIVE AND SELF-ORGANIZING SYSTEMS WORKSHOPS, PROCEEDINGS,
  • Bagnoli, F., Guazzini, A. and Lio, P., 2008. Human Heuristics for Autonomous Agents BIO-INSPIRED COMPUTING AND COMMUNICATION, v. 5151
  • Lu, XF., Hui, P., Lio, P. and Xiong, Z., 2008. Identity Privacy Protection by Delayed Transmission in Pocket Switched Networks EUC 2008: PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON EMBEDDED AND UBIQUITOUS COMPUTING, VOL 2, WORKSHOPS,
  • Lio, P., Brilli, M. and Fani, R., 2008. Topological metrics in Blast data mining: Plasmid and nitrogen-fixing proteins case studies BIOINFORMATICS RESEARCH AND DEVELOPMENT, PROCEEDINGS, v. 13
  • Kershenbaum, A., Pappas, V., Lee, KW., Lio, P., Sadler, B. and Verma, D., 2008. A Biologically-Inspired MANET Architecture Proceedings of SPIE, the International Society for Optical Engineering,
  • Nguyen, VA., Koukolikova-Nicola, Z., Bagnoli, F. and Lio, P., 2008. Bayesian Inference on Hidden Knowledge in High-Throughput Molecular Biology Data PRICAI 2008: TRENDS IN ARTIFICIAL INTELLIGENCE, v. 5351
  • van der Wath, RC. and Lio, P., 2008. A Stochastic Single Cell Based Model of BrdU Measured Hematopoietic Stem Cell Kinetics COMPUTATIONAL METHODS IN SYSTEMS BIOLOGY, PROCEEDINGS, v. 5307
  • Lu, YE., Lio, P. and Hand, S., 2007. Beta random projection ISM WORKSHOPS 2007: NINTH IEEE INTERNATIONAL SYMPOSIUM ON MULTIMEDIA - WORKSHOPS, PROCEEDINGS,
    Doi: http://doi.org/10.1109/ISM.Workshops.2007.61
  • Sguanci, L., Bagnoli, F. and Lio, P., 2007. Modeling HIV quasispecies evolutionary dynamics BMC EVOLUTIONARY BIOLOGY, v. 7
    Doi: http://doi.org/10.1186/1471-2148-7-S2-S5
  • Angelini, C., Cutillo, L., De Feis, I., Van der Wath, R. and Lio, P., 2007. Identifying regulatory sites using neighborhood species Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, Proceedings, v. 4447
  • Lawniczak, AT., Lio, P., Xie, S. and Xu, JY., 2007. Wavelet spectral analysis of packet traffic near phase transition point from free flow to congestion in data network model 2007 CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING, VOLS 1-3,
  • Carapelli, A., Lio, P., Nardi, F., van der Wath, E. and Frati, F., 2007. Phylogenetic analysis of mitochondrial protein coding genes confirms the reciprocal paraphyly of Hexapoda and Crustacea BMC EVOLUTIONARY BIOLOGY, v. 7
    Doi: http://doi.org/10.1186/1471-2148-7-S2-S8
  • Fani, R., Brilli, M., Fondi, M. and Lio, P., 2007. The role of gene fusions in the evolution of metabolic pathways: the histidine biosynthesis case BMC EVOLUTIONARY BIOLOGY, v. 7
    Doi: http://doi.org/10.1186/1471-2148-7-S2-S4
  • Milanesi, L., Lio, P. and Breton, V., 2007. Bioinformatics Challenges in Life Science IST-Africa 2007 Conference Proceedings, Paul Cunningham and Miriam Cunningham (Eds), IIMC International Information Management Corporation, 2007, ISBN: 1-905824-04-1,
  • Lu, YE., Hand, S. and Lio, P., 2007. Keyword searching in structured overlays via content distance addressing Databases, Information Systems, and Peer-to-Peer Computing, v. 4125
  • Sguanci, L., Lio, P. and Bagnoli, F., 2006. The influence of risk perception in epidemics: A cellular agent model CELLULAR AUTOMATA, PROCEEDINGS, v. 4173
  • Sguanci, L., Lio, P. and Bagnoli, F., 2006. Modeling evolutionary dynamics of HIV infection COMPUTATIONAL METHODS IN SYSTEMS BIOLOGY, PROCEEDINGS, v. 4210
  • Fani, R., Caramelli, D. and Lio, P., 2006. It happened... From prebiotic chemistry to human evolution Rivista di biologia,
  • Lu, YE., Hand, S. and Lio, P., 2005. Keyword searching in hypercubic manifolds Fifth IEEE International Conference on Peer-to-Peer Computing, Proceedings,
  • Lio, P., 2005. Phylogenetic and structural analysis of mitochondrial complex I proteins GENE, v. 345
    Doi: http://doi.org/10.1016/j.gene.2004.11.033
  • Lio, P. and Vannucci, M., 2003. Investigating the evolution and structure of chemokine receptors GENE, v. 317
    Doi: http://doi.org/10.1016/S0378-1119(03)00666-8
  • Brilli, M., Lio, P., Lazcano, A. and Fani, R., 2002. Evolution of TIM barrel: Multiple gene elongation events in HisA. Origins of Life and Evolution of the Biosphere, v. 22
  • Lio, P., 2002. Structure and evolution of the histidine biosynthetic pathway Origins of Life and Evolution of the Biosphere, v. 22
  • Hagelberg, E., Kayser, M., Nagy, M., Roewer, L., Zimdahl, H., Krawczak, M., Lió, P. and Schiefenhövel, W., 1999. Molecular genetic evidence for the human settlement of the Pacific: analysis of mitochondrial DNA, Y chromosome and HLA markers. Philos Trans R Soc Lond B Biol Sci, v. 354
    Doi: http://doi.org/10.1098/rstb.1999.0367
  • Dewar, J., Wheatley, A., Wilkinson, J., Holgate, ST., Thomas, NS., Lio, P., Morton, NE. and Hall, IP., 1997. Association of the Gln 27 beta(2)-adrenoceptor polymorphism and IgE variability in asthmatic families CHEST, v. 111
  • Morton, NE. and Lio, P., 1997. Oligogenic linkage and map integration GENETIC MAPPING OF DISEASE GENES,
  • Thomas, NS., Wilkinson, J., Lio, P., Doull, I., Morton, NE. and Holgate, ST., 1997. Investigation of the genetic factors underlying asthma and atopy in outbred UK populations 5TH WEST-PACIFIC ALLERGY SYMPOSIUM / 7TH KOREA-JAPAN JOINT ALLERGY SYMPOSIUM,
  • Bagnoli, F., Guasti, G. and Lio, P., 1995. Translation optimization in bacteria: Statistical models NONLINEAR EXCITATIONS IN BIOMOLECULES,
  • Fani, R., Grifoni, A., Damiani, G., Lio, P. and Mori, E., 1994. Nucleotide Sequence of Azospirillum RAPD markers Azospirillum VI and Related Microorganisms:: Genetics - Physiology - Ecology (NATO ASI Series / Ecological Sciences),
  • Fani, R., Bandi, C., Bazzicalupo, M., Damiani, G., Di Cello, F., Fancelli, S., Gerace, L., Grifoni, A., Lio, P. and Mori, E., 1994. Phylogenetic Studies of the Genus Azospirillum Related Microorganisms:: Genetics - Physiology - Ecology (NATO ASI Series / Ecological Sciences),
  • Azevedo, T., Passamonti, L., Lio, P. and Toschi, N., A Machine Learning Tool for Interpreting Differences in Cognition Using Brain Features IFIP Advances in Information and Communication Technology,
    Doi: http://doi.org/10.1007/978-3-030-19823-7_40
  • Deasy, J., Ercole, A. and Liò, P., Adaptive Prediction Timing for Electronic Health Records
  • Lio, P., Long Range Properties of DNA Sequences Collana Franco Angeli Editore,
  • Wang, D., Jamnik, M. and Lio, P., Investigating diagrammatic reasoning with deep neural networks
    Doi: 10.1007/978-3-319-91376-6_36
  • Nguyen, VA. and Lio, P., Filling in the gaps of biological network
  • Angione, C., Bartocci, E., Bortolussi, L., Lio, P., Occhipinti, A. and Sanguinetti, G., Bayesian Design for Whole Cell Synthetic Biology Models Proceedings of the Third International Workshop on Hybrid Systems Biology (HSB 2014),
  • Rossi, E., Monti, F., Bronstein, M. and Liò, P., ncRNA Classification with Graph Convolutional Networks
  • Taylor, D., Spasov, S. and Liò, P., Co-Attentive Cross-Modal Deep Learning for Medical Evidence Synthesis and Decision Making
  • Angione, C., Pratanwanich, N. and Lio, P., A hybrid of multi-omics FBA and Bayesian factor modeling to identify pathway crosstalks Proceedings of the 6th International Workshop on Bio-Design Automation (IWBDA),
  • Webb, E., Day, B., Andres-Terre, H. and Lió, P., Factorised Neural Relational Inference for Multi-Interaction Systems
  • Prokhorov, V., Pilehvar, M., Kartsaklis, D., Lio, P. and Collier, N., Unseen Word Representation by Aligning Heterogeneous Lexical Semantic Spaces
  • Bakas, S., Reyes, M., Jakab, A., Bauer, S., Rempfler, M., Crimi, A., Shinohara, RT., Berger, C., Ha, SM., Rozycki, M., Prastawa, M., Alberts, E., Lipkova, J., Freymann, J., Kirby, J., Bilello, M., Fathallah-Shaykh, H., Wiest, R., Kirschke, J., Wiestler, B., Colen, R., Kotrotsou, A., Lamontagne, P., Marcus, D., Milchenko, M., Nazeri, A., Weber, M-A., Mahajan, A., Baid, U., Gerstner, E., Kwon, D., Acharya, G., Agarwal, M., Alam, M., Albiol, A., Albiol, A., Albiol, FJ., Alex, V., Allinson, N., Amorim, PHA., Amrutkar, A., Anand, G., Andermatt, S., Arbel, T., Arbelaez, P., Avery, A., Azmat, M., Pranjal, B., Bai, W., Banerjee, S., Barth, B., Batchelder, T., Batmanghelich, K., Battistella, E., Beers, A., Belyaev, M., Bendszus, M., Benson, E., Bernal, J., Bharath, HN., Biros, G., Bisdas, S., Brown, J., Cabezas, M., Cao, S., Cardoso, JM., Carver, EN., Casamitjana, A., Castillo, LS., Catà, M., Cattin, P., Cerigues, A., Chagas, VS., Chandra, S., Chang, Y-J., Chang, S., Chang, K., Chazalon, J., Chen, S., Chen, W., Chen, JW., Chen, Z., Cheng, K., Choudhury, AR., Chylla, R., Clérigues, A., Colleman, S., Colmeiro, RGR., Combalia, M., Costa, A., Cui, X., Dai, Z., Dai, L., Daza, LA., Deutsch, E., Ding, C., Dong, C., Dong, S., Dudzik, W., Eaton-Rosen, Z., Egan, G., Escudero, G., Estienne, T., Everson, R., Fabrizio, J., Fan, Y., Fang, L., Feng, X., Ferrante, E., Fidon, L., Fischer, M., French, AP., Fridman, N., Fu, H., Fuentes, D., Gao, Y., Gates, E., Gering, D., Gholami, A., Gierke, W., Glocker, B., Gong, M., González-Villá, S., Grosges, T., Guan, Y., Guo, S., Gupta, S., Han, W-S., Han, IS., Harmuth, K., He, H., Hernández-Sabaté, A., Herrmann, E., Himthani, N., Hsu, W., Hsu, C., Hu, X., Hu, X., Hu, Y., Hu, Y., Hua, R., Huang, T-Y., Huang, W., Huffel, SV., Huo, Q., Vivek, HV., Iftekharuddin, KM., Isensee, F., Islam, M., Jackson, AS., Jambawalikar, SR., Jesson, A., Jian, W., Jin, P., Jose, VJM., Jungo, A., Kainz, B., Kamnitsas, K., Kao, P-Y., Karnawat, A., Kellermeier, T., Kermi, A., Keutzer, K., Khadir, MT., Khened, M., Kickingereder, P., Kim, G., King, N., Knapp, H., Knecht, U., Kohli, L., Kong, D., Kong, X., Koppers, S., Kori, A., Krishnamurthi, G., Krivov, E., Kumar, P., Kushibar, K., Lachinov, D., Lambrou, T., Lee, J., Lee, C., Lee, Y., Lee, M., Lefkovits, S., Lefkovits, L., Levitt, J., Li, T., Li, H., Li, W., Li, H., Li, X., Li, Y., Li, H., Li, Z., Li, X., Li, Z., Li, X., Li, W., Lin, Z-S., Lin, F., Lio, P., Liu, C., Liu, B., Liu, X., Liu, M., Liu, J., Liu, L., Llado, X., Lopez, MM., Lorenzo, PR., Lu, Z., Luo, L., Luo, Z., Ma, J., Ma, K., Mackie, T., Madabushi, A., Mahmoudi, I., Maier-Hein, KH., Maji, P., Mammen, CP., Mang, A., Manjunath, BS., Marcinkiewicz, M., McDonagh, S., McKenna, S., McKinley, R., Mehl, M., Mehta, S., Mehta, R., Meier, R., Meinel, C., Merhof, D., Meyer, C., Miller, R., Mitra, S., Moiyadi, A., Molina-Garcia, D., Monteiro, MAB., Mrukwa, G., Myronenko, A., Nalepa, J., Ngo, T., Nie, D., Ning, H., Niu, C., Nuechterlein, NK., Oermann, E., Oliveira, A., Oliveira, DDC., Oliver, A., Osman, AFI., Ou, Y-N., Ourselin, S., Paragios, N., Park, MS., Paschke, B., Pauloski, JG., Pawar, K., Pawlowski, N., Pei, L., Peng, S., Pereira, SM., Perez-Beteta, J., Perez-Garcia, VM., Pezold, S., Pham, B., Phophalia, A., Piella, G., Pillai, GN., Piraud, M., Pisov, M., Popli, A., Pound, MP., Pourreza, R., Prasanna, P., Prkovska, V., Pridmore, TP., Puch, S., Puybareau, É., Qian, B., Qiao, X., Rajchl, M., Rane, S., Rebsamen, M., Ren, H., Ren, X., Revanuru, K., Rezaei, M., Rippel, O., Rivera, LC., Robert, C., Rosen, B., Rueckert, D., Safwan, M., Salem, M., Salvi, J., Sanchez, I., Sánchez, I., Santos, HM., Sartor, E., Schellingerhout, D., Scheufele, K., Scott, MR., Scussel, AA., Sedlar, S., Serrano-Rubio, JP., Shah, NJ., Shah, N., Shaikh, M., Shankar, BU., Shboul, Z., Shen, H., Shen, D., Shen, L., Shen, H., Shenoy, V., Shi, F., Shin, HE., Shu, H., Sima, D., Sinclair, M., Smedby, O., Snyder, JM., Soltaninejad, M., Song, G., Soni, M., Stawiaski, J., Subramanian, S., Sun, L., Sun, R., Sun, J., Sun, K., Sun, Y., Sun, G., Sun, S., Suter, YR., Szilagyi, L., Talbar, S., Tao, D., Tao, D., Teng, Z., Thakur, S., Thakur, MH., Tharakan, S., Tiwari, P., Tochon, G., Tran, T., Tsai, YM., Tseng, K-L., Tuan, TA., Turlapov, V., Tustison, N., Vakalopoulou, M., Valverde, S., Vanguri, R., Vasiliev, E., Ventura, J., Vera, L., Vercauteren, T., Verrastro, CA., Vidyaratne, L., Vilaplana, V., Vivekanandan, A., Wang, G., Wang, Q., Wang, CJ., Wang, W., Wang, D., Wang, R., Wang, Y., Wang, C., Wang, G., Wen, N., Wen, X., Weninger, L., Wick, W., Wu, S., Wu, Q., Wu, Y., Xia, Y., Xu, Y., Xu, X., Xu, P., Yang, T-L., Yang, X., Yang, H-Y., Yang, J., Yang, H., Yang, G., Yao, H., Ye, X., Yin, C., Young-Moxon, B., Yu, J., Yue, X., Zhang, S., Zhang, A., Zhang, K., Zhang, X., Zhang, L., Zhang, X., Zhang, Y., Zhang, L., Zhang, J., Zhang, X., Zhang, T., Zhao, S., Zhao, Y., Zhao, X., Zhao, L., Zheng, Y., Zhong, L., Zhou, C., Zhou, X., Zhou, F., Zhu, H., Zhu, J., Zhuge, Y., Zong, W., Kalpathy-Cramer, J., Farahani, K., Davatzikos, C., Leemput, KV. and Menze, B., Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
  • Bardozzo, F., Lio', P. and Tagliaferri, R., A machine learning approach to investigate regulatory control circuits in bacterial metabolic pathways
  • Scata', M., Di Stefano, A., Giacchi, E., La Corte, A. and Lio, P., The Bio-Inspired and Social Evolution of Node and Data in a Multilayer Network SCITEPRESS Digital Library,
  • Kazhdan, D., Dimanov, B., Jamnik, M., Lio, P. and Weller, A., Now You See Me (CME): Concept-based Model Extraction
  • Dmitry, K., Shams, Z. and Pietro, L., MARLeME: A Multi-Agent Reinforcement Learning Model Extraction Library. 2020 International Joint Conference on Neural Networks (IJCNN),
    Doi: http://doi.org/10.1109/IJCNN48605.2020.9207564
  • Opolka, FL., Solomon, A., Cangea, C., Veličković, P., Liò, P. and Hjelm, RD., Spatio-Temporal Deep Graph Infomax
  • Fernandes, P., Lio, P. and Milanesi, L., Challenges in building an e-health infrastructure for P5 Medicine
  • Veličković, P., Fedus, W., Hamilton, WL., Liò, P., Bengio, Y. and Hjelm, RD., Deep Graph Infomax
  • Zhu, J., Yang, G. and Lio, P., How Can We Make GAN Perform Better in Single Medical Image Super-Resolution? A Lesion Focused Multi-Scale Approach 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019),
  • Cangea, C., Belilovsky, E., Liò, P. and Courville, A., VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering
  • Books

  • Aiello, LM., Cherifi, C., Cherifi, H., Lambiotte, R., Lió, P. and Rocha, LM., 2019. Preface
  • Aiello, LM., Cherifi, C., Cherifi, H., Lambiotte, R., Lió, P. and Rocha, LM., 2019. Preface
  • Lio, P. and Zuliani, P., 2019. Automated Reasoning for Systems Biology and Medicine Preface
  • Bartocci, E., Lio, P. and Paoletti, N., 2016. Preface
  • Di Serio, C., Liò, P., Nonis, A. and Tagliaferri, R., 2015. Preface
  • Lio, P. and Verma, D., 2011. Biologically Inspired Networking and Sensing
  • Internet publications

  • Viñas, R., Andrés-Terré, H., Liò, P. and Bryson, K., 2019. Adversarial generation of gene expression data
    Doi: 10.1101/836254
  • Bica, I., Andrés-Terré, H., Cvejic, A. and Liò, P., Unsupervised generative and graph representation learning for modelling cell differentiation
    Doi: 10.1101/801605
  • Zhao, Y., Wang, D., Gao, X., Mullins, R., Lio, P. and Jamnik, M., Probabilistic Dual Network Architecture Search on Graphs
  • Wang, D., Jamnik, M. and Lio, P., Extrapolatable Relational Reasoning With Comparators in Low-Dimensional Manifolds
  • Luzhnica, E., Day, B. and Liò, P., On Graph Classification Networks, Datasets and Baselines
  • Book chapters

  • Vijayakumar, S., Conway, M., Lió, P. and Angione, C., 2018. Optimization of Multi-Omic Genome-Scale Models: Methodologies, Hands-on Tutorial, and Perspectives.
    Doi: http://doi.org/10.1007/978-1-4939-7528-0_18
  • Felicetti, LF., Femminella, MF., Lio', LP., Reali, RG. and Lio, P., 2017. Effect of Aging, Disease Versus Health Conditions in the Design of Nano-communications in Blood Vessels
    Doi: http://doi.org/10.1007/978-3-319-50688-3_19
  • Lio, P., Bianchi, L., Nguyen, V. and Kitchovich, S., 2013. Risk Perception, Heuristics and Epidemic Spread
  • Bansal, A., Azad, S. and Lio, P., 2013. Malaria incidence forecasting and its implication to intervention strategies in South East Asia Region
    Doi: 10.1007/978-3-319-00395-5_110
  • Lio, P. and Brilli, M., 2010. Transcription factors and gene regulatory networks
  • Emiliani, G., Fondi, M., Lio, P. and Fani, R., 2010. Evolution of Metabolic Pathways and Evolution of Genomes
  • Brilli, M. and Lio, P., 2010. The structural and dynamical properties of biological systems
  • Brilli, M., Fani, R. and Lio, P., 2010. Bioinformatics of gene families
  • Carapelli, A., Nardi, F., Dallai, R., Boore, JL., Lio, P. and Frati, F., 2005. Relationships between hexapods and crustaceans based on 4 mitochondrial genes
  • Renato Fani, RF., Silvia Casadei, SC. and Lio, P., 2002. Origin and Evolution of nif Genes
    Doi: http://doi.org/10.1007/0-306-47615-0_85
  • Theses / dissertations

  • Wang, D., Neural Diagrammatic Reasoning
  • Andres Terre, H., Interpreting Deep Learning for cell differentiation. Supervised and Unsupervised models viewed through the lens of information and perturbation theory.
  • Dimanov, B., Interpretable Deep Learning: Beyond Feature-Importance with Concept-based Explanations
  • Contact Details

    Room: 
    FC20
    Office phone: 
    (01223) 7-63604
    Email: 

    pl219at@cam.ac.uk