Journal articles
Sathyanarayanan, A., Mueller, TT., Ali Moni, M., Schueler, K., ECNP TWG Network members, , Baune, BT., Lio, P., Mehta, D., Baune, BT., Dierssen, M., Ebert, B., Fabbri, C., Fusar-Poli, P., Gennarelli, M., Harmer, C., Howes, OD., Janzing, JGE., Lio, P., Maron, E., Mehta, D., Minelli, A., Nonell, L., Pisanu, C., Potier, M-C., Rybakowski, F., Serretti, A., Squassina, A., Stacey, D., van Westrhenen, R. and Xicota, L., 2023. Multi-omics data integration methods and their applications in psychiatric disorders. Eur Neuropsychopharmacol, v. 69
Doi: http://doi.org/10.1016/j.euroneuro.2023.01.001
Waqas, M., Aziz, S., Liò, P., Khan, Y., Ali, A., Iqbal, A., Khan, F. and Almajhdi, FN., 2023. Immunoinformatics design of multivalent epitope vaccine against monkeypox virus and its variants using membrane-bound, enveloped, and extracellular proteins as targets. Front Immunol, v. 14
Doi: http://doi.org/10.3389/fimmu.2023.1091941
Islam, MS., Hasan, KF., Sultana, S., Uddin, S., Lio', P., Quinn, JMW. and Moni, MA., 2023. HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN. Neural Netw, v. 162
Doi: 10.1016/j.neunet.2023.03.004
Del Duca, S., Semenzato, G., Esposito, A., Liò, P. and Fani, R., 2023. The Operon as a Conundrum of Gene Dynamics and Biochemical Constraints: What We Have Learned from Histidine Biosynthesis. Genes (Basel), v. 14
Doi: http://doi.org/10.3390/genes14040949
Bongini, P., Scarselli, F., Bianchini, M., Dimitri, GM., Pancino, N. and Lio, P., 2023. Modular Multi-Source Prediction of Drug Side-Effects With DruGNN. IEEE/ACM Trans Comput Biol Bioinform, v. 20
Doi: 10.1109/TCBB.2022.3175362
Buterez, D., Janet, JP., Kiddle, SJ. and Liò, P., 2023. MF-PCBA: Multifidelity High-Throughput Screening Benchmarks for Drug Discovery and Machine Learning. J Chem Inf Model, v. 63
Doi: 10.1021/acs.jcim.2c01569
Charoenkwan, P., Pipattanaboon, C., Nantasenamat, C., Hasan, MM., Moni, MA., Lio', P. and Shoombuatong, W., 2023. PSRTTCA: A new approach for improving the prediction and characterization of tumor T cell antigens using propensity score representation learning. Comput Biol Med, v. 152
Doi: http://doi.org/10.1016/j.compbiomed.2022.106368
Ciravegna, G., Barbiero, P., Giannini, F., Gori, M., Liò, P., Maggini, M. and Melacci, S., 2023. Logic Explained Networks Artificial Intelligence, v. 314
Doi: http://doi.org/10.1016/j.artint.2022.103822
Yang, J., Li, X-X., Liu, F., Nie, D., Lio, P., Qi, H. and Shen, D., 2023. Fast Multi-Contrast MRI Acquisition by Optimal Sampling of Information Complementary to Pre-Acquired MRI Contrast. IEEE Trans Med Imaging, v. 42
Doi: 10.1109/TMI.2022.3227262
Petrović, A., Nikolić, M., Bugarić, U., Delibašić, B. and Lio, P., 2023. Controlling highway toll stations using deep learning, queuing theory, and differential evolution Engineering Applications of Artificial Intelligence, v. 119
Doi: http://doi.org/10.1016/j.engappai.2022.105683
Lu, X., Liao, Y., Liu, C., Lio, P. and Hui, P., 2022. Heterogeneous Model Fusion Federated Learning Mechanism Based on Model Mapping IEEE Internet of Things Journal, v. 9
Doi: 10.1109/JIOT.2021.3110908
Charoenkwan, P., Schaduangrat, N., Hasan, MM., Moni, MA., Lió, P. and Shoombuatong, W., 2022. Empirical comparison and analysis of machine learning-based predictors for predicting and analyzing of thermophilic proteins. EXCLI J, v. 21
Doi: 10.17179/excli2022-4723
Lio, P., Simpson, E., Pierce, E., Cronin, A., McLean, R., Dave, SS., Kovacik, AJ., Feely, M. and Silverberg, J., 2022. 33273 Impact of atopic dermatitis lesion locations on patient burden: A real-world study Journal of the American Academy of Dermatology, v. 87
Doi: 10.1016/j.jaad.2022.06.727
Barbero, F., Bodnar, C., Borde, HSDO., Bronstein, M., Veličković, P. and Liò, P., 2022. Sheaf Neural Networks with Connection Laplacians
Charoenkwan, P., Schaduangrat, N., Lio', P., Moni, MA., Shoombuatong, W. and Manavalan, B., 2022. Computational prediction and interpretation of druggable proteins using a stacked ensemble-learning framework. iScience, v. 25
Doi: http://doi.org/10.1016/j.isci.2022.104883
Chen, Y., Schonlieb, CB., Lio, P., Leiner, T., Dragotti, PL., Wang, G., Rueckert, D., Firmin, D. and Yang, G., 2022. AI-Based Reconstruction for Fast MRI-A Systematic Review and Meta-Analysis Proceedings of the IEEE, v. 110
Doi: 10.1109/JPROC.2022.3141367
Liu, L., Huang, Z., Liò, P., Schönlieb, C-B. and Aviles-Rivero, AI., 2022. PC-SwinMorph: Patch Representation for Unsupervised Medical Image
Registration and Segmentation
Tullos, KZ., Barta, K., Lio, P. and Winders, T., 2022. 171 International survey: Effects of cumulative exposure to corticosteroids in patients with eczema, including topical steroid withdrawal syndrome (TSWS) Journal of Investigative Dermatology, v. 142
Doi: 10.1016/j.jid.2022.05.178
Huang, J., Fang, Y., Nan, Y., Wu, H., Wu, Y., Gao, Z., Li, Y., Wang, Z., Lio, P., Rueckert, D., Eldar, YC. and Yang, G., 2022. Data and Physics Driven Learning Models for Fast MRI -- Fundamentals and
Methodologies from CNN, GAN to Attention and Transformers
Yi, K., Chen, J., Wang, YG., Zhou, B., Liò, P., Fan, Y. and Hamann, J., 2022. Approximate Equivariance SO(3) Needlet Convolution
Azevedo, T., Bethlehem, RAI., Whiteside, D., Swaddiwudhipong, N., Rowe, J., Lió, P. and Rittman, T., 2022. Identifying healthy individuals with Alzheimer neuroimaging phenotypes in the UK Biobank
Doi: 10.1101/2022.01.05.22268795
Charoenkwan, P., Schaduangrat, N., Lio', P., Moni, MA., Manavalan, B. and Shoombuatong, W., 2022. NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides. Comput Biol Med, v. 148
Doi: 10.1016/j.compbiomed.2022.105700
Shadbahr, T., Roberts, M., Stanczuk, J., Gilbey, J., Teare, P., Dittmer, S., Thorpe, M., Torne, RV., Sala, E., Lio, P., Patel, M., Collaboration, AIX-COVNET., Rudd, JHF., Mirtti, T., Rannikko, A., Aston, JAD., Tang, J. and Schönlieb, C-B., 2022. Classification of datasets with imputed missing values: does imputation
quality matter?
Wang, Y., Wang, YG., Hu, C., Li, M., Fan, Y., Otter, N., Sam, I., Gou, H., Hu, Y., Kwok, T., Zalcberg, J., Boussioutas, A., Daly, RJ., Montúfar, G., Liò, P., Xu, D., Webb, GI. and Song, J., 2022. Cell graph neural networks enable the precise prediction of patient survival in gastric cancer. NPJ Precis Oncol, v. 6
Doi: http://doi.org/10.1038/s41698-022-00285-5
Dimitri, GM., Spasov, S., Duggento, A., Passamonti, L., Lió, P. and Toschi, N., 2022. Multimodal and multicontrast image fusion via deep generative models Information Fusion, v. 88
Doi: http://doi.org/10.1016/j.inffus.2022.07.017
Dhillon, SK., Ganggayah, MD., Sinnadurai, S., Lio, P. and Taib, NA., 2022. Theory and Practice of Integrating Machine Learning and Conventional Statistics in Medical Data Analysis. Diagnostics (Basel), v. 12
Doi: http://doi.org/10.3390/diagnostics12102526
Lu, M., Christensen, C., Weber, J., Konno, T., Läubli, N., Scherer, K., Avezov, E., Lio, P., Lapkin, A., Kaminski Schierle, G. and Kaminski, C., 2022. ERnet: a tool for the semantic segmentation and quantitative analysis of endoplasmic reticulum topology for video-rate super-resolution imaging
Doi: 10.1101/2022.05.17.492189
Chaturvedi, A., Tiwari, A., Chaturvedi, S. and Lio, P., 2022. System Neural Network: Evolution and Change Based Structure Learning IEEE Transactions on Artificial Intelligence, v. 3
Doi: http://doi.org/10.1109/TAI.2022.3143778
Charoenkwan, P., Chumnanpuen, P., Schaduangrat, N., Lio', P., Moni, MA. and Shoombuatong, W., 2022. Improved prediction and characterization of blood-brain barrier penetrating peptides using estimated propensity scores of dipeptides. J Comput Aided Mol Des, v. 36
Doi: http://doi.org/10.1007/s10822-022-00476-z
Zafeiriou, S., Bronstein, M., Cohen, T., Vinyals, O., Song, L., Leskovec, J., Lio, P., Bruna, J. and Gori, M., 2022. Guest Editorial: Non-Euclidean Machine Learning IEEE Transactions on Pattern Analysis and Machine Intelligence, v. 44
Doi: 10.1109/TPAMI.2021.3129857
Magister, LC., Barbiero, P., Kazhdan, D., Siciliano, F., Ciravegna, G., Silvestri, F., Jamnik, M. and Lio, P., 2022. Encoding Concepts in Graph Neural Networks
Charoenkwan, P., Schaduangrat, N., Moni, MA., Lio', P., Manavalan, B. and Shoombuatong, W., 2022. SAPPHIRE: A stacking-based ensemble learning framework for accurate prediction of thermophilic proteins. Comput Biol Med, v. 146
Doi: http://doi.org/10.1016/j.compbiomed.2022.105704
Aslam, AA., Baksh, RA., Pape, SE., Strydom, A., Gulliford, MC., Chan, LF. and GO-DS21 Consortium, , 2022. Diabetes and Obesity in Down Syndrome Across the Lifespan: A Retrospective Cohort Study Using U.K. Electronic Health Records. Diabetes Care, v. 45
Doi: 10.2337/dc22-0482
Dodson, J. and Lio, PA., 2022. Biologics and Small Molecule Inhibitors: an Update in Therapies for Allergic and Immunologic Skin Diseases. Curr Allergy Asthma Rep,
Doi: http://doi.org/10.1007/s11882-022-01047-w
Pisanu, C., Severino, G., De Toma, I., Dierssen, M., Fusar-Poli, P., Gennarelli, M., Lio, P., Maffioletti, E., Maron, E., Mehta, D., Minelli, A., Potier, M-C., Serretti, A., Stacey, D., van Westrhenen, R., Xicota, L., European College of Neuropsychopharmacology (ECNP) Pharmacogenomics & Transcriptomics Network, , Baune, BT. and Squassina, A., 2022. Transcriptional biomarkers of response to pharmacological treatments in severe mental disorders: A systematic review. Eur Neuropsychopharmacol, v. 55
Doi: 10.1016/j.euroneuro.2021.12.005
Rafidi, B., Kondapi, K., Beestrum, M., Basra, S. and Lio, P., 2022. Psychological Therapies and Mind-Body Techniques in the Management of Dermatologic Diseases: A Systematic Review. Am J Clin Dermatol, v. 23
Doi: http://doi.org/10.1007/s40257-022-00714-y
Azevedo, T., Campbell, A., Romero-Garcia, R., Passamonti, L., Bethlehem, RAI., Liò, P. and Toschi, N., 2022. A deep graph neural network architecture for modelling spatio-temporal dynamics in resting-state functional MRI data. Med Image Anal, v. 79
Doi: http://doi.org/10.1016/j.media.2022.102471
Charoenkwan, P., Chiangjong, W., Nantasenamat, C., Moni, MA., Lio', P., Manavalan, B. and Shoombuatong, W., 2022. SCMTHP: A New Approach for Identifying and Characterizing of Tumor-Homing Peptides Using Estimated Propensity Scores of Amino Acids. Pharmaceutics, v. 14
Doi: 10.3390/pharmaceutics14010122
Barta, K., Fonacier, LS., Hart, M., Lio, P., Tullos, K., Sheary, B. and Winders, TA., 2022. Corticosteroid exposure and cumulative effects in patients with eczema: Results from a patient survey. Ann Allergy Asthma Immunol,
Doi: 10.1016/j.anai.2022.09.031
Zago, E., Dal Molin, A., Dimitri, GM., Xumerle, L., Pirazzini, C., Bacalini, MG., Maturo, MG., Azevedo, T., Spasov, S., Gómez-Garre, P., Periñán, MT., Jesús, S., Baldelli, L., Sambati, L., Calandra-Buonaura, G., Garagnani, P., Provini, F., Cortelli, P., Mir, P., Trenkwalder, C., Mollenhauer, B., Franceschi, C., Liò, P., Nardini, C. and PROPAG-AGEING Consortium, , 2022. Early downregulation of hsa-miR-144-3p in serum from drug-naïve Parkinson's disease patients. Sci Rep, v. 12
Doi: http://doi.org/10.1038/s41598-022-05227-6
Tong, C., Rocheteau, E., Veličković, P., Lane, N. and Liò, P., 2022. Predicting Patient Outcomes with Graph Representation Learning Studies in Computational Intelligence, v. 1013
Doi: 10.1007/978-3-030-93080-6_20
Oykhman, P., Dookie, J., Al-Rammahy, H., de Benedetto, A., Asiniwasis, RN., LeBovidge, J., Wang, J., Ong, PY., Lio, P., Gutierrez, A., Capozza, K., Martin, SA., Frazier, W., Wheeler, K., Boguniewicz, M., Spergel, JM., Greenhawt, M., Silverberg, JI., Schneider, L. and Chu, DK., 2022. Dietary Elimination for the Treatment of Atopic Dermatitis: A Systematic Review and Meta-Analysis. J Allergy Clin Immunol Pract, v. 10
Doi: http://doi.org/10.1016/j.jaip.2022.06.044
Charoenkwan, P., Ahmed, S., Nantasenamat, C., Quinn, JMW., Moni, MA., Lio', P. and Shoombuatong, W., 2022. AMYPred-FRL is a novel approach for accurate prediction of amyloid proteins by using feature representation learning. Sci Rep, v. 12
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Bodnar, C., Giovanni, FD., Chamberlain, BP., Liò, P. and Bronstein, MM., 2022. Neural Sheaf Diffusion: A Topological Perspective on Heterophily and
Oversmoothing in GNNs
Reich, K., Lio, PA., Bissonnette, R., Alexis, AF., Lebwohl, MG., Pink, AE., Kabashima, K., Boguniewicz, M., Nowicki, RJ., Valdez, H., Zhang, F., DiBonaventura, M., Cameron, MC. and Clibborn, C., 2022. Magnitude and Time Course of Response to Abrocitinib for Moderate-to-Severe Atopic Dermatitis. J Allergy Clin Immunol Pract,
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Yang, J., Küstner, T., Hu, P., Liò, P. and Qi, H., 2022. End-to-End Deep Learning of Non-rigid Groupwise Registration and Reconstruction of Dynamic MRI. Front Cardiovasc Med, v. 9
Doi: http://doi.org/10.3389/fcvm.2022.880186
Coggan, H., Andres Terre, H. and Liò, P., 2022. A novel interpretable machine learning algorithm to identify optimal parameter space for cancer growth. Front Big Data, v. 5
Doi: 10.3389/fdata.2022.941451
Lu, X., Xue, A., Lio, P. and Hui, P., 2022. Intelligent Decision Making Based on the Combination of Deep Reinforcement Learning and an Influence Map Applied Sciences (Switzerland), v. 12
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Patel, S., Patel, S., Shah, RM., Shah, S., Doshi, S. and Lio, PA., 2022. Engagement in sun-protective practices based on health insurance coverage: A cross-sectional analysis. J Am Acad Dermatol,
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Charoenkwan, P., Schaduangrat, N., Lio, P., Moni, MA., Chumnanpuen, P. and Shoombuatong, W., 2022. iAMAP-SCM: A Novel Computational Tool for Large-Scale Identification of Antimalarial Peptides Using Estimated Propensity Scores of Dipeptides. ACS Omega, v. 7
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Patel, S., Patel, S., Shah, RM., Doshi, S., Shah, S. and Lio, PA., 2022. Effects of sun protection on serum vitamin D deficiency. Photodermatol Photoimmunol Photomed,
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Buffelli, D., Liò, P. and Vandin, F., 2022. SizeShiftReg: a Regularization Method for Improving Size-Generalization
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Lu, X., Yang, F., Zou, L., Lio, P. and Hui, P., 2022. An LTE Authentication and Key Agreement Protocol Based on the ECC Self-Certified Public Key IEEE/ACM Transactions on Networking,
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Ahamad, MM., Aktar, S., Uddin, MJ., Rashed-Al-Mahfuz, M., Azad, AKM., Uddin, S., Alyami, SA., Sarker, IH., Khan, A., Liò, P., Quinn, JMW. and Moni, MA., 2022. Adverse Effects of COVID-19 Vaccination: Machine Learning and Statistical Approach to Identify and Classify Incidences of Morbidity and Postvaccination Reactogenicity. Healthcare (Basel), v. 11
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Christensen, CN., Lu, M., Ward, EN., Lio, P. and Kaminski, CF., 2022. Spatio-temporal Vision Transformer for Super-resolution Microscopy
Yang, AF., Chun, KS., Yu, L., Walter, JR., Kim, D., Lee, JY., Jeong, H., Keller, MC., Seshadri, DR., Olagbenro, MO., Bae, JW., Reuther, W., Wu, E., Okamoto, K., Ikoma, A., Lio, PA., Fishbein, AB., Paller, AS. and Xu, S., 2022. Validation of a hand-mounted wearable sensor for scratching movements in adults with atopic dermatitis. J Am Acad Dermatol,
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Schaduangrat, N., Anuwongcharoen, N., Moni, MA., Lio', P., Charoenkwan, P. and Shoombuatong, W., 2022. StackPR is a new computational approach for large-scale identification of progesterone receptor antagonists using the stacking strategy. Sci Rep, v. 12
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Ayorinde, JOO., Citterio, F., Landrò, M., Peruzzo, E., Islam, T., Tilley, S., Taylor, G., Bardsley, V., Liò, P., Samoshkin, A. and Pettigrew, GJ., 2022. Artificial Intelligence You Can Trust: What Matters Beyond Performance When Applying Artificial Intelligence to Renal Histopathology? J Am Soc Nephrol, v. 33
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Charoenkwan, P., Nantasenamat, C., Hasan, MM., Moni, MA., Lio', P., Manavalan, B. and Shoombuatong, W., 2022. StackDPPIV: A novel computational approach for accurate prediction of dipeptidyl peptidase IV (DPP-IV) inhibitory peptides. Methods, v. 204
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Ahmad, S., Charoenkwan, P., Quinn, JMW., Moni, MA., Hasan, MM., Lio', P. and Shoombuatong, W., 2022. SCORPION is a stacking-based ensemble learning framework for accurate prediction of phage virion proteins. Sci Rep, v. 12
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Kwatra, SG., De Bruin-Weller, M., Lio, P., Deleuran, M., Ofori, S., Teixeira, HD., Calimlim, B., Liu, Y. and Weidinger, S., 2022. 33152 Targeted combined endpoint improvement in patient and disease domains in atopic dermatitis (AD) among adults with moderate-to-severe AD treated with upadacitinib Journal of the American Academy of Dermatology, v. 87
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Dimitri, GM., Meoni, G., Tenori, L., Luchinat, C. and Lió, P., 2022. NMR Spectroscopy Combined with Machine Learning Approaches for Age Prediction in Healthy and Parkinson’s Disease Cohorts through Metabolomic Fingerprints Applied Sciences (Switzerland), v. 12
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Borgheresi, R., Barucci, A., Colantonio, S., Aghakhanyan, G., Assante, M., Bertelli, E., Carlini, E., Carpi, R., Caudai, C., Cavallero, D., Cioni, D., Cirillo, R., Colcelli, V., Dell'Amico, A., Di Gangi, D., Erba, PA., Faggioni, L., Falaschi, Z., Gabelloni, M., Gini, R., Lelii, L., Liò, P., Lorito, A., Lucarini, S., Manghi, P., Mangiacrapa, F., Marzi, C., Mazzei, MA., Mercatelli, L., Mirabile, A., Mungai, F., Miele, V., Olmastroni, M., Pagano, P., Paiar, F., Panichi, G., Pascali, MA., Pasquinelli, F., Shortrede, JE., Tumminello, L., Volterrani, L., Neri, E. and NAVIGATOR Consortium Group, , 2022. NAVIGATOR: an Italian regional imaging biobank to promote precision medicine for oncologic patients. Eur Radiol Exp, v. 6
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Buterez, D., Bica, I., Tariq, I., Andrés-Terré, H. and Liò, P., 2022. CellVGAE: an unsupervised scRNA-seq analysis workflow with graph attention networks. Bioinformatics, v. 38
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Meoni, G., Tenori, L., Schade, S., Licari, C., Pirazzini, C., Bacalini, MG., Garagnani, P., Turano, P., PROPAG-AGEING Consortium, , Trenkwalder, C., Franceschi, C., Mollenhauer, B. and Luchinat, C., 2022. Metabolite and lipoprotein profiles reveal sex-related oxidative stress imbalance in de novo drug-naive Parkinson's disease patients. NPJ Parkinsons Dis, v. 8
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Lio, P., Anjuwon, S., Grivet-Seyve, M. and Emesiani, C., 2022. 33954 Efficacy, tolerability, and acceptability of a balm formulated with dimethicone 1% in type II diabetes patients with dry, cracked skin Journal of the American Academy of Dermatology, v. 87
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Goh, CWJ., Bodnar, C. and Liò, P., 2022. Simplicial Attention Networks
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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
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Corso, G., Ying, R., Pandy, M., Veličković, P., Leskovec, J. and Lio, P., 2021. Neural Distance Embeddings for Biological Sequences Advances in Neural Information Processing Systems, v. 22
Lio, P., Eichenfield, L., Guttman, E., Piguet, V. and Simpson, E., 2021. 28081 Strategies to improve quality of atopic dermatitis care in North America: Results from the Atopic Dermatitis Quality of Care (ADQoC) initiative Journal of the American Academy of Dermatology, v. 85
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Castiglione, F., Deb, D., Srivastava, AP., Liò, P. and Liso, A., 2021. From Infection to Immunity: Understanding the Response to SARS-CoV2 Through In-Silico Modeling. Front Immunol, v. 12
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Agnihotri, G., Lio, PA. and Lee, KC., 2021. 27880 Differences in pediatric vs adult clinical trial designs for atopic dermatitis Journal of the American Academy of Dermatology, v. 85
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Vecchio, AD., Deac, A., Liò, P. and Veličković, P., 2021. Neural message passing for joint paratope-epitope prediction
Amor, A., Lio', P., Singh, V., Torné, RV. and Terre, HA., 2021. Graph Representation Learning on Tissue-Specific Multi-Omics
Lu, X., Wang, F., Jiang, C. and Lio, P., 2021. A universal malicious documents static detection framework based on feature generalization Applied Sciences (Switzerland), v. 11
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Lio, P., Soung, J., Cather, J., Casillas, M., Ding, Y., De Lozier, AM., Chen, Y-F. and Simpson, E., 2021. 26691 Rapid and concurrent improvements in the signs and symptoms of atopic dermatitis with baricitinib in the phase 3 study, BREEZE-AD5 Journal of the American Academy of Dermatology, v. 85
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Bodnar, C., Day, B. and Lió, P., Proximal Distilled Evolutionary Reinforcement Learning AAAI 2020 - 34th AAAI Conference on Artificial Intelligence,
Laise, P., Fanelli, D., Lio, P. and Arcangeli, A., Modeling TGF-β signaling pathway in epithelial-mesenchymal transition AIP Advances, v. Special Topic: Physics of Cancer
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Conference proceedings
Lu, X., Zhang, X. and Lio, P., 2023. GAT-DNS: DNS Multivariate Time Series Prediction Model Based on Graph Attention Network ACM Web Conference 2023 - Companion of the World Wide Web Conference, WWW 2023,
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Cardozo, S., Montero, GI., Kazhdan, D., Dimanov, B., Wijaya, M., Jamnik, M. and Lio, P., 2022. Explainer Divergence Scores (EDS): Some Post-Hoc Explanations May be Effective for Detecting Unknown Spurious Correlations CEUR Workshop Proceedings, v. 3318
Day, B., Vinas, R., Simidjievski, N. and Lio, P., 2022. Attentional Meta-learners for Few-shot Polythetic Classification INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 162,
Fan, J., Pei, J., Bi, X., Xiao, B. and Lio, P., 2022. Context Correlation Aware Network for Cardiac Segmentation Proceedings - IEEE International Conference on Multimedia and Expo, v. 2022-July
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Lu, X. and Lio, P., 2022. Second International Workshop On Artificial Intelligence To Security - AITS 2022 Proceedings - 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshop Volume, DSN-W 2022,
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Manouchehrinia, A., Ebrahimi, A., Wiil, UK., Kiani, NA., Lio, P., Olsson, T. and Kockum, I., 2022. A susceptibility network analysis of disease pathways leading to multiple sclerosis MULTIPLE SCLEROSIS JOURNAL, v. 28
Qian, P., Yang, J., Lió, P., Hu, P. and Qi, H., 2022. Joint Group-Wise Motion Estimation and Segmentation of Cardiac Cine MR Images Using Recurrent U-Net Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 13413 LNCS
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Opolka, FL. and Lio, P., 2022. Bayesian Link Prediction with Deep Graph Convolutional Gaussian Processes INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 151, v. 151
Barbiero, P., Ciravegna, G., Giannini, F., Lió, P., Gori, M. and Melacci, S., 2022. Entropy-Based Logic Explanations of Neural Networks Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022, v. 36
Opolka, FL., Zhi, Y-C., Lio, P. and Dong, X., 2022. Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 151, v. 151
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Jain, R., Ciravegna, G., Barbiero, P., Giannini, F., Buffelli, D. and Lio, P., 2022. Extending Logic Explained Networks to Text Classification Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022,
Aghakhanyan, G., Barucci, A., Colantonio, S., Colcelli, V., Pasquinelli, F., Gini, R., Lio, P., Mazzei, M., Erba, P., Miele, V. and Neri, E., 2022. NAVIGATOR: An Imaging Biobank to Precisely Prevent and Predict cancer, and facilitate the Participation of oncologic patients to Diagnosis and Treatment EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, v. 49
Tailor, SA., Opolka, FL., Liò, P. and Lane, ND., 2022. DO WE NEED ANISOTROPIC GRAPH NEURAL NETWORKS? ICLR 2022 - 10th International Conference on Learning Representations,
Lu, X., Zhao, J. and Lio, P., 2022. Robust android malware detection based on subgraph network and denoising GCN network MobiSys 2022 - Proceedings of the 2022 20th Annual International Conference on Mobile Systems, Applications and Services,
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Lu, X., Pang, R. and Lio, P., 2022. Poster: CFMAP: A Robust CPU Clock Fingerprint Model for Device Authentication Proceedings of the ACM Conference on Computer and Communications Security,
Doi: http://doi.org/10.1145/3548606.3563528
Campbell, A., Qendro, L., Liò, P. and Mascolo, C., 2022. ROBUST AND EFFICIENT UNCERTAINTY AWARE BIOSIGNAL CLASSIFICATION VIA EARLY EXIT ENSEMBLES ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, v. 2022-May
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Tilly, T., Auckland, K., Nibhani, R., Martin, J., Nihr, N., Morrell, NW., Lio', P. and Graf, S., 2022. Deep learning of regulatory regions discovers enhancer variants implicated in PAH EUROPEAN RESPIRATORY JOURNAL, v. 60
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Liu, L., Huang, Z., Liò, P., Schönlieb, CB. and Aviles-Rivero, AI., 2022. You only Look at Patches: A Patch-wise Framework for 3D Unsupervised Medical Image Registration Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 13386 LNCS
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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
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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,
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
Liò, P., 2013. Methodologies for Systems Medicine: Time to Join the Forces of Bioengineering and Bioinformatics. BIOINFORMATICS,
2012. Artificial Immune Systems - 11th International Conference, ICARIS 2012, Taormina, Italy, August 28-31, 2012. Proceedings ICARIS, v. 7597
Kim, H., Khoo, WM. and Lio, P., 2012. Polymorphic Attacks against Sequence-based Software Birthmarks
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
2011. Artificial Immune Systems - 10th International Conference, ICARIS 2011, Cambridge, UK, July 18-21, 2011. Proceedings ICARIS, v. 6825
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
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
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),
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
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
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
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,
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
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,
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)
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., 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
Bella, G. and Lio, P., 2009. Formal Analysis of the Genetic Toggle COMPUTATIONAL METHODS IN SYSTEMS BIOLOGY, PROCEEDINGS, v. 5688
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
Sorathiyar, A., Lio, P. and Sguanci, L., 2009. Mathematical Model of HIV Superinfection and Comparative Drug Therapy ARTIFICIAL IMMUNE SYSTEMS, PROCEEDINGS, v. 5666
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,
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 Case Study of ICA with Multi-scale PCA of Simulated Traffic Data ARTIFICIAL NEURAL NETWORKS - ICANN 2009, PT II, v. 5769
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
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
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
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,
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,
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,
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, YE., Lio, P. and Hand, S., 2008. Beta Random Projection BIO-INSPIRED COMPUTING AND COMMUNICATION, v. 5151
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
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
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,
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
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
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
van der Wath, RC. and Lio, P., 2008. A Stochastic Multi-agent Model of Stem Cell Proliferation CELLULAR AUTOMATA, PROCEEDINGS, v. 5191
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
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
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
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,
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
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
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,
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
Sguanci, L., Lio, P. and Bagnoli, F., 2006. The influence of risk perception in epidemics: A cellular agent model CELLULAR AUTOMATA, PROCEEDINGS, v. 4173
Fani, R., Caramelli, D. and Lio, P., 2006. It happened... From prebiotic chemistry to human evolution Rivista di biologia,
Sguanci, L., Lio, P. and Bagnoli, F., 2006. Modeling evolutionary dynamics of HIV infection COMPUTATIONAL METHODS IN SYSTEMS BIOLOGY, PROCEEDINGS, v. 4210
Lu, YE., Hand, S. and Lio, P., 2005. Keyword searching in hypercubic manifolds Fifth IEEE International Conference on Peer-to-Peer Computing, Proceedings,
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
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,
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
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),
Cangea, C., Belilovsky, E., Liò, P. and Courville, A., VideoNavQA: Bridging the Gap between Visual and Embodied Question
Answering
Norcliffe, A., Bodnar, C., Day, B., Moss, J. and Liò, P., Neural ODE Processes
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
Bardozzo, F., Lio', P. and Tagliaferri, R., A machine learning approach to investigate regulatory control circuits in bacterial metabolic pathways
Kazhdan, D., Dimanov, B., Jamnik, M., Lio, P. and Weller, A., Now You See Me (CME): Concept-based Model Extraction
Taylor, D., Spasov, S. and Liò, P., Co-Attentive Cross-Modal Deep Learning for Medical Evidence Synthesis and Decision Making
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
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),
Espinosa Zarlenga, M., Barbiero, P., Ciravegna, G., Marra, G., Giannini, F., Diligenti, M., Shams, Z., Precioso, F., Melacci, S., Weller, A., Lio, P. and Jamnik, M., Concept embedding models: Beyond the Accuracy-Explainability Trade-Off
Webb, E., Day, B., Andres-Terre, H. and Lió, P., Factorised Neural Relational Inference for Multi-Interaction Systems
Lio, P., Long Range Properties of DNA Sequences Collana Franco Angeli Editore,
Prokhorov, V., Pilehvar, M., Kartsaklis, D., Lio, P. and Collier, N., Unseen Word Representation by Aligning Heterogeneous Lexical Semantic Spaces
Nguyen, VA. and Lio, P., Filling in the gaps of biological network
Drotár, P., Jamasb, AR., Day, B., Cangea, C. and Liò, P., Structure-aware generation of drug-like molecules
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,
Deasy, J., Ercole, A. and Liò, P., Adaptive Prediction Timing for Electronic Health Records
Moss, JD., Opolka, FL., Dumitrascu, B. and Lió, P., Approximate Latent Force Model Inference
Fernandes, P., Lio, P. and Milanesi, L., Challenges in building an e-health infrastructure for P5 Medicine
Opolka, FL., Solomon, A., Cangea, C., Veličković, P., Liò, P. and Hjelm, RD., Spatio-Temporal Deep Graph Infomax
Veličković, P., Fedus, W., Hamilton, WL., Liò, P., Bengio, Y. and Hjelm, RD., Deep Graph Infomax
Margeloiu, A., Simidjievski, N., Lio, P. and Jamnik, M., Weight predictor network with feature selection for small sample tabular biomedical data
Scherer, P., Lio, P. and Jamnik, M., Distributed representations of graphs for drug pair scoring Proceedings of the First Learning on Graphs Conference (LoG 2022), v. PMLR 198
Angione, C., Carapezza, G., Costanza, J., Lio, P. and Nicosia, G., Computing with Metabolic Machines EPiC Series in Computing,
Doi: 10.29007/t48n
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),
Internet publications
Igashov, I., Jamasb, A., Sadek, A., Sverrisson, F., Schneuing, A., Liò, P., Blundell, T., Bronstein, M. and Correia, B., 2022. Decoding Surface Fingerprints for Protein-Ligand Interactions
Doi: 10.1101/2022.04.26.489341
Zhao, Y., Wang, D., Gao, X., Mullins, R., Lio, P. and Jamnik, M., 2020. Probabilistic Dual Network Architecture Search on Graphs
Wang, D., Jamnik, M. and Lio, P., 2020. Extrapolatable Relational Reasoning With Comparators in Low-Dimensional
Manifolds
Luzhnica, E., Day, B. and Liò, P., 2019. On Graph Classification Networks, Datasets and Baselines
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., 2019. Unsupervised generative and graph representation learning for modelling cell differentiation
Doi: 10.1101/801605
Book chapters
DE MARIA, E., DESPEYROUX, J., FELTY, A., LIÒ, P., OLARTE, C. and BAHRAMI, A., 2022. Logique calculatoire pour la biomédecine et les neurosciences
Doi: 10.51926/iste.9029.ch6
Vignani, R., Scali, M. and Liò, P., 2022. Molecular Markers and Genomics for Food and Beverages Characterization
Doi: 10.1007/978-981-16-4318-7_43
Barsacchi, M., Andres-Terré, H. and Lió, P., 2022. Metabolically driven latent space learning for gene expression data
Doi: 10.1142/9781800610941_0005
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
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., Bianchi, L., Nguyen, V. and Kitchovich, S., 2013. Risk Perception, Heuristics and Epidemic Spread
Lio, P. and Verma, D., 2012. Biologically Inspired Networking and Sensing: Algorithms and Architectures Preface
Brilli, M., Fani, R. and Lio, P., 2010. Bioinformatics of gene families
Brilli, M. and Lio, P., 2010. The structural and dynamical properties of biological systems
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
Carapelli, A., Nardi, F., Dallai, R., Boore, J., LiÒ, P. and Frati, F., 2005. Relationships between hexapods and crustaceans based on four mitochondrial genes
Doi: 10.1201/9781420037548.ch12
Carapelli, A., Nardi, F., Dallai, R., Boore, JL., Lio, P. and Frati, F., 2005. Relationships between hexapods and crustaceans based on 4 mitochondrial genes
Liò, P., Bazzicalupo, M., Grifoni, A., Mori, E. and Fani, R., 1995. Cloning and Analysis of an Azospirillum brasilense Iteron and hslUV Operon Containing Region
Doi: 10.1007/978-3-642-79906-8_14
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
Theses / dissertations
Deasy, J., Relaxing assumptions in deep probabilistic modelling
Azevedo, T., Data-driven Representations in Brain Science: Modelling Approaches in Gene Expression and Neuroimaging Domains
Spivakovsky-Gonzalez, P., Computational Tools for Metabolic Modeling and Gene Duplication Analysis
Andres Terre, H., Interpreting Deep Learning for cell differentiation. Supervised and Unsupervised models viewed through the lens of information and perturbation theory.
Wang, D., Neural Diagrammatic Reasoning
Spasov, S., Encoding parameter and structural efficiency in deep learning
Dimanov, B., Interpretable Deep Learning: Beyond Feature-Importance with Concept-based Explanations
Rocheteau, E., Representation Learning for Patients in the Intensive Care Unit
