[j47]Abbaspour Onari M., Jahangoshai Rezaee M., Sabri M., Nobile M.S.: An explainable data-driven decision support framework for strategic customer development, Knowledge-Based Systems, 11761, 2024 (online first)
[j46]Grochowalski P., Kosior D., Kozioł W., Pękala B., Kaymak U., Fuchs C., Nobile M.S.: Python library for interval-valued fuzzy inference, SoftwareX, 2024 (online first)
[j45]Chicco D., Spolaor S., Nobile M.S.: Ten quick tips for fuzzy logic modeling of biomedical systems, PLOS Computational Biology, 19(12): e1011700, 2023
[j44]Botta C., Perez C., Larrayoz M., Puig N., Cedena M., Termini R., Goicoechea I., Rodriguez S., Zabaleta A., Lopez A., Sarvide S., Blanco L., Papetti D.M., Nobile M.S., Besozzi D., Gentile M., Correale P., Siragusa S., Oriol A., González-Garcia M.E., Sureda A., de Arriba F., Tamayo F.R., Moraleda J., Gironella M., Hernandez M.T., Bargay J., Palomera L., Pérez-Montaña A., Goldschmidt H., Avet-Loiseau H., Roccaro A., Orfao A., Martinez-Lopez J., Rosiñol L., Lahuerta J., Blade J., Mateos M., San-Miguel J.F., Martinez Climent J., Paiva B., the Programa Para el Estudio de la Terapéutica en Hemopatías Malignas/Grupo Español de Mieloma (PETHEMA/GEM) cooperative group & the iMMunocell study group: Large T cell clones expressing immune checkpoints increase during multiple myeloma evolution and predict treatment resistance, Nature Communications, 14(1):5825, 2023
[j43]Nobile M.S., Manzoni L., Ashlock D.A., Qu R.: Models of representation in Computational Intelligence [guest editorial], IEEE Computational Intelligence Magazine, 18(1):20-21, 2023
[j42]Lupi A., Spolaor S., Favero A., Bello L., Stramare R., Pegoraro E., Nobile M.S.: Muscle magnetic resonance characterization of STIM1 tubular aggregate myopathy using unsupervised learning, PLOS ONE, 18(5): e0285422, 2023
[j41]Papetti D.M., Spolaor S., Tirelli A., Leonardi T., Caprioli C., Besozzi D., Vlachou T., Pelicci P.G., Cazzaniga P., Nobile M.S.: Barcode demultiplexing of nanopore sequencing raw signals by unsupervised machine learning, Frontiers in Bioinformatics, 3:1067113, 2023
[j40]Perinot E., Fritz J., Fusani L., Voelkl B., Nobile M.S.: Characterization of bird formations using fuzzy modeling, Journal of the Royal Society Interface, 20:20220798, 2023
[j39]Papetti D.M., van Abeelen K., Davies R., Menè R., Heilbron F., Perelli F.P., Artico J., Seraphim A., Moon J.C., Parati G., Xue H., Kellman P., Badano L.P., Besozzi D., Nobile M.S., Torlasco C.: An accurate and time-efficient deep learning-based system for automated segmentation and reporting of Cardiac Magnetic Resonance-detected ischemic scar, Computer Methods and Programs in Biomedicine, 229:107321, 2023
[j38]Nobile M.S., Capitoli G., Sowirono V., Clerici F., Piga I., van Abeelen K., Magni F., Pagni F., Galimberti S., Cazzaniga P., and Besozzi D.: Unsupervised Neural Networks as a support tool for pathology diagnosis in MALDI-MSI experiments: a case study on thyroid biopsies, Expert Systems with Applications, 215:119296, 2022
[j37]Nobile M.S., Papetti D.M., Spolaor S., Cazzaniga P., and Manzoni L.: Shaping and dilating the fitness landscape for parameter estimation in stochastic biochemical models, Applied Sciences, 12(13):6671, 2022
[j36]Spolaor S., Rovetta M., Nobile M.S., Cazzaniga P., Tisi R., Besozzi D.: Modeling calcium signaling in S. cerevisiae highlights the role and regulation of the calmodulin-calcineurin pathway in response to hypotonic shock, Frontiers in Molecular Biosciences, 9:856030, 2022
[j35]Riva S.G., Cazzaniga P., Nobile M.S., Spolaor S., Rundo L., Besozzi D., Tangherloni A.: SMGen: generator of synthetic models of biochemical reaction networks, Symmetry, 14(1):119, 2022
[j34]Castelli M., Manzoni L., Mariot L., Nobile M.S., Tangherloni A.: Salp Swarm Optimization: a critical review, Expert Systems with Applications, 189:116029, 2022
[j33]Tangherloni A., Nobile M.S., Cazzaniga P., Capitoli G., Spolaor S., Rundo L., Mauri G., Besozzi D.: FiCoS: a fine-grained and coarse-grained GPU-powered deterministic simulator for biochemical networks, PLOS Computational Biology, 17(9):e1009410, 2021
[j32]Nobile M.S., Cazzaniga P., Ramazzotti D.: Investigating the performance of multi-objective optimization when learning Bayesian Networks, Neurocomputing, 461:281–291, 2021
[j31]Nobile M.S., Fontana F., Manzoni L., Cazzaniga P., Mauri G., Saracino G.A.A., Besozzi D., Gelain F.: HyperBeta: characterizing the structural dynamics of proteins and self-assembling peptides, Scientific Reports, 11:7783, 2021
[j30]Spolaor S., Scheve M., Firat M., Cazzaniga P., Besozzi D., Nobile M.S.: Screening for combination cancer therapies with dynamic fuzzy modeling and multi-objective optimization, Frontiers in Genetics – Computational Genomics, 12:449, 2021
[j29]Nobile M.S., Coelho V., Pescini D., Damiani C.: Accelerated global sensitivity analysis of genome-wide constraint-based metabolic models, BMC Bioinformatics, 22:78, 2021
[j28]Sacco E., Tisi R., Spinelli M., Palmioli A., Airoldi C., Cazzaniga P., Besozzi D., Nobile M.S., Mazzoleni E., Arnhold S., De Gioia L., Grandori R., Peri F., Vanoni M.: The multi-level mechanism of action of a pan-Ras inhibitor explains its antiproliferative activity on Cetuximab-resistant cancer cells, Frontiers in Molecular Biosciences, 8:21, 2021
[j27]Rundo L., Tangherloni A., Cazzaniga P., Mistri M., Galimberti S., Woitek R., Sala E., Mauri G., Nobile M.S.: A CUDA-powered method for the feature extraction and unsupervised analysis of medical images, Journal of Supercomputing, 77:8514–8531, 2021
[j26]Fuchs C., Nobile M.S., Zamora G., Degeneffe A., Kubben P., Kaymak U.: Tremor assessment using smartphone sensor data and fuzzy reasoning, BMC Bioinformatics, 22:57, 2020
[j25]Spolaor S., Fuchs C., Cazzaniga P., Kaymak U., Besozzi D., Nobile M.S.: Simpful: a user-friendly Python library for fuzzy logic, International Journal of Computational Intelligence Systems, 13(1):1687–1698, 2020
[j24]Rundo L., Tangherloni A., Tyson D.R., Betta R., Militello C., Spolaor S., Nobile M.S., Besozzi D., Lubbock A.L.R., Quaranta V., Mauri G., Lopez C.F., Cazzaniga P.: ACDC: Automated Cell Detection and Counting for time-lapse fluorescence microscopy, Applied Sciences, 10(18):6187, 2020
[j23]Nobile M.S., Nisoli E., Vlachou T., Spolaor S., Cazzaniga P., Mauri G., P.G. Pelicci, D. Besozzi: cuProCell: GPU-accelerated analysis of cell proliferation with flow cytometry data, IEEE Journal of Biomedical And Health Informatics, 24(11):3173–3181, 2020
[j22]Manzoni L., Papetti D.M., Cazzaniga P., Spolaor S., Mauri G., Besozzi D., Nobile M.S.: Surfing on fitness landscapes: a boost on optimization by Fourier surrogate modeling, Entropy, 22(3):285, 2020
[j21]Nobile M.S., Votta G., Palorini R., Spolaor S., De Vitto H., Cazzaniga P., Ricciardiello F., Mauri G., Alberghina L., Chiaradonna F., Besozzi D.: Fuzzy modeling and global optimization to predict novel therapeutic targets in cancer cells, Bioinformatics, 36(7):2181–2188, 2020
[j20]Rundo L., Han C., Nagano Y., Zhang J., Hataya R., Militiello C., Tangherloni A., Nobile M.S., Ferretti C., Besozzi D., Gilardi M.C., Vitabile S., Mauri G., Nakayama H., Cazzaniga P.: USE-Net: incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets, Neurocomputing, 365:31–43, 2019
[j19]Besozzi D., Castelli M., Cazzaniga P., Manzoni L., Nobile M.S., Ruberto S., Rundo L., Spolaor S., Tangherloni A., Vanneschi L.: Computational Intelligence for Life Sciences, Fundamenta Informaticae, 171(1-4):57–80, 2020
[j18]Spolaor S., Nobile M.S., Mauri G., Cazzaniga P., Besozzi D.: Coupling mechanistic approaches and Fuzzy Logic to model and simulate complex systems, IEEE Transactions on Fuzzy Systems, 28(8):1748–1759, 2020
[j17]Tangherloni A., Spolaor S., Cazzaniga P., Besozzi D., Rundo L., Mauri G., Nobile M.S.: Biochemical parameter estimation vs. benchmark functions: a comparative study of optimization performance and representation design, Applied Soft Computing, 81:105494, 2019
[j16]Rundo L., Tangherloni A., Cazzaniga P., Nobile M.S., Russo G., Gilardi M.C., Vitabile S., Mauri G., Besozzi D., Militello C.: A novel framework for MR image segmentation and quantification based on MedGA, Computer Methods and Programs in Biomedicine, 176:159–172, 2019
[j15]Nobile M.S., Vlachou T., Spolaor S., Bossi D., Cazzaniga P., Lanfrancone L., Mauri G., Pelicci P.G., Besozzi D.: Modeling cell proliferation in human acute myeloid leukemia xenografts, Bioinformatics, 35(18):3378–3386, 2019
[j14]Rundo L., Tangherloni A., Nobile M.S., Militello C., Besozzi D., Mauri G., Cazzaniga P.: MedGA: a novel evolutionary method for medical image enhancement, Expert Systems with Applications, 119:387–399, 2019
[j13]Ramazzotti D., Nobile M.S., Antoniotti M., Graudenzi A.: Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena, Journal of Computational Science, 30:1–10, 2019
[j12]Nobile M.S., Cazzaniga P., Besozzi D., Mauri G.: ginSODA: massive parallel integration of stiff ODE systems on GPUs, Journal of Supercomputing, 75(12):7844–7856, 2019
[j11]Tangherloni A., Spolaor S., Rundo L., Nobile M.S., Cazzaniga P., Mauri G., Liò P., Merelli I., Besozzi D.: GenHap: A novel computational method based on genetic algorithms for haplotype assembly, BMC Bioinformatics, 20(4):172, 2019
[j10]Nobile M.S., Cazzaniga P., Besozzi D., Colombo R., Mauri G., Pasi G.: Fuzzy Self-Tuning PSO: a settings-free algorithm for global optimization, Swarm and Evolutionary Computation, 39:70–85, 2018
[j9]Harris L.A., Nobile M.S., Pino J.C., Lubbock A.L.R., Besozzi D., Mauri G., Cazzaniga P., Lopez C.F.: GPU-powered model analysis with PySB/cupSODA, Bioinformatics, 33(21):3492–3494, 2017
[j8]Nobile M.S., Porreca A.E., Spolaor S., Manzoni L., Cazzaniga P., Mauri G., Besozzi D.: Efficient simulation of reaction systems on Graphics Processing Units, Fundamenta Informaticae, 154:307–321, 2017
[j7]Tangherloni A., Nobile M.S., Cazzaniga P., Besozzi D., Mauri G.: LASSIE: Simulating large-scale models of biochemical systems on GPUs, BMC Bioinformatics, 18(1):246, 2017
[j6]Nobile M.S., Cazzaniga P., Tangherloni A., Besozzi D.: Graphics Processing Units in Bioinformatics, Computational Biology and Systems Biology, Briefings in Bioinformatics, 18(5):870–885, 2017
[j5]Tangherloni A., Nobile M.S., Cazzaniga P., Besozzi D., Mauri G.: Gillespie’s Stochastic Simulation Algorithm on MIC coprocessors, Journal of Supercomputing, 73(2):676–686, 2017
[j4]Cazzaniga P., Damiani C., Besozzi D., Colombo R., Nobile M.S., Gaglio D., Pescini D., Molinari S., Mauri G., Alberghina L., Vanoni M.: Computational strategies for a system-level understanding of metabolism, Metabolites, 4(4):1034–1087, 2014
[j3]Nobile M.S., Cazzaniga P., Besozzi D., Pescini D., Mauri G.: cuTauLeaping: a GPU-powered tau-leaping stochastic simulator for massive parallel analyses of biological systems, PLoS ONE, 9(3):e91963, 2014
[j2]Cazzaniga P., Nobile M.S., Besozzi D., Bellini M., Mauri G.: Massive exploration of perturbed conditions of the Blood Coagulation Cascade through GPU parallelization, BioMed Research International, vol. 2014, Article ID 863298, 2014
[j1]Nobile M.S., Cazzaniga P., Besozzi D., Mauri G.: GPU-accelerated simulations of mass-action kinetics models with cupSODA, Journal of Supercomputing, 69(1):17–24, 2014
[c60]Bacciu L., Cazzaniga P., Gallese C., Fuchs C., Kaymak U., Papetti D.M., Nobile M.S.: Our fruitful relationship with Sugeno inference, from FUMOSO to pyFUME, accepted to the 20th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2024), Lisbon, Portugal (2024, accepted)
[c59]Pękala B., Grochowalskii P., Kosior D., Gil D., Kozioł W., Dyczkowski K., Kaymak U., Fuchs C., Nobile M.S.: Applications of IFIS python library in interval-valued fuzzy inference problems, FUZZ-IEEE 2024, Yokohama, Japan (accepted)
[c58]Abbaspour Onari M., Grau I., Nobile M.S., Zhang Y.: Trustworthy Artificial Intelligence in Medical Applications: A Mini Survey, Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2023), Eindhoven, The Netherlands
[c57]Della Torre S., Cavallotto G., Besozzi D., Gervasi M., La Vacca G., Nobile M.S., Rancoita P.G.: Advantages of GPU-accelerated approach for solving the Parker equation in the heliosphere, Proceedings of the 38th International Cosmic Ray Conference (ICRC2023), vol. 444, Nagoya, Japan
[c56]Rizzo M., Veneri A., Albarelli A., Lucchese C., Nobile M.S., Conati C.: A theoretical framework for AI models explainability with application in biomedicine, Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2023), Eindhoven, The Netherlands
[c55]Gallese C., Scantamburlo T., Manzoni L., Nobile M.S.: Investigating semi-automatic assessment of data sets fairness by means of fuzzy logic, Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2023), Eindhoven, The Netherlands
[c54]Papetti D.M., Fuchs C., Coelho V., Kaymak U., Nobile M.S.: Estimation of fuzzy models from mixed data sets with pyFUME, Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2023), Eindhoven, The Netherlands
[c53]Bianchi A., Di Marco A., Marzi F., Stilo G., Pellegrini C., Masi S., Mengozzi A., Virdis A., Nobile M.S., Simeoni M.: Trustworthy Machine Learning predictions to support clinical research and decisions, proceedings of the IEEE 36th International Symposium on Computer Based Medical Systems (IEEE CBMS 2023), L’Aquila, Italy
[c52]Coelho V., Papetti D.M., Tangherloni A., Cazzaniga P., Besozzi D., Nobile M.S.: The domination game: dilating bubbles to fill up Pareto fronts, Proceedings of the 2023 IEEE Congress on Evolutionary Computation (IEEE CEC 2023), Chicago, IL, USA
[c51]Fuchs C., Spolaor S., Kaymak U., and Nobile M.S.: The impact of variable selection and transformation on the interpretability and accuracy of fuzzy models, Proceedings of the 19th IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2022), Ottawa, ON, Canada
[c50]Papetti D.M., Coelho V., Ashlock D.A., Cazzaniga P., Spolaor S., Besozzi D., and Nobile M.S.: Local bubble dilation functions: hypersphere-bounded landscape deformations simplify global optimization, Proceedings of the 19th IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2022) , Ottawa, ON, Canada
[c49]Gallese C., Fuchs C., Riva S.G., Foglia E., Schettini F., Ferrario L., Falletti E., and Nobile M.S.: Predicting and characterizing legal claims of hospitals with Computational Intelligence: the legal and ethical implications, Proceedings of the 19th IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2022) , Ottawa, ON, Canada
[c48]Abbaspour Onari M., Nobile M.S., Grau Garcia I., Fuchs C., Zhang Y., Boer A.-K., and Scharnhorst V.: Comparing interpretable AI approaches for the clinical environment: an application to COVID-19, Proceedings of the 19th IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2022) , Ottawa, ON, Canada
[c47]Fuchs C., Nobile M.S., Kaymak U.: Building interpretable and parsimonious fuzzy models using a multi-objective approach, Proceedings of the World Congress of Computational Intelligence (IEEE WCCI 2022), Padua, Italy
[c46]Perinot E., Fritz J., Fusani L., Voelkl B., Nobile M.S: Characterizing the flying behaviour of bird flocks with fuzzy reasoning, accepted to 13th International Workshop on Fuzzy Logic and Applications (WILF 2021)
[c45]Spolaor S., Papetti D.M., Cazzaniga P., Besozzi D., Nobile M.S.: Identification of Pareto-optimal drug target combinations in cancer cell models, Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB), 2021
[c44]Papetti D.M., Ashlock D.A., Cazzaniga P., Besozzi D., Nobile M.S.: If you can’t beat it, squash it: Simplify global optimization by evolving dilation functions, IEEE Congress on Evolutionary Computation (IEEE CEC), 2021
[c43]Tangherloni A., Riva S.G., Spolaor S., Besozzi D., Nobile M.S., Cazzaniga P.: The impact of representations in the optimization of marker panels for single-cell RNA data, IEEE Congress on Evolutionary Computation (IEEE CEC), 2021
[c42]Gallese C., Falletti E., Nobile M.S., Ferrario L., Schettini F., and Foglia E.: Preventing litigation with a predictive model of COVID-19 ICUs occupancy, Fourth Annual Workshop on Applications of Artificial Intelligence in the Legal Industry, IEEE BigData, 2020
[c41]Nobile M.S.: Fuzzy Self-Tuning PSO: Single-objective global optimization without moving a finger, Workshop on Evolutionary and Population-based Optimization (WEPO 2020), 19th International Conference of the Italian Association for Artificial Intelligence (AIxIA), 2020
[c40]Nobile M.S., Cazzaniga P., Spolaor S., Besozzi D., Manzoni L.: Fourier surrogate models of dilated fitness landscapes in Systems Biology (or how we learned to torture optimization problems until they confess), IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2020), 2020
[c39]Papetti D.M., Spolaor S., Besozzi D., Cazzaniga P., Antoniotti M., Nobile M.S.: On the automatic training of fully analogical spiking neuromorphic chips, IEEE International Joint Conference on Neural Networks (IJCNN 2020), Glasgow, UK, 2020
[c38]Nobile M.S., Spolaor S., Cazzaniga P., Papetti D.M., Besozzi D., Ashlock D.A., Manzoni L.: Which random is the best random? A study on sampling methods in Fourier surrogate modeling, IEEE Congress on Evolutionary Computation (CEC 2020), Glasgow, UK, 2020
[c37]Fuchs C., Spolaor S., Nobile M.S., Kaymak U.: pyFUME: a python package for fuzzy model estimation, International Conference on Fuzzy Systems (FUZZ-IEEE 2020), Glasgow, UK, 2020
[c36]Fuchs C., Spolaor S., Nobile M.S., Kaymak U.: A graph theory approach to fuzzy rule base simplification, 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2020), Lisboa, Portugal, Communications in Computer and Information Science book series (CCIS), vol. 1237, pp. 387–401 , 2020
[c35]Spolaor S., Fuchs C., Kaymak U., Nobile M.S.: A novel multi-objective approach to fuzzy clustering, Proceedings of the 2019 IEEE Symposium Series on Computational Intelligence (SSCI 2019), Xiamen, China, 2020
[c34]Rundo L., Tangherloni A., Galimberti S., Cazzaniga P., Woitek R., Sala E., Nobile M.S., Mauri G.: HaraliCU: GPU-Powered Haralick feature extraction on medical images exploiting the full dynamics of gray-scale levels, Proceedings of the 15th International Conference on Parallel Computing Technologies (PaCT 2019), Almaty, Kazakhstan, Lecture Notes on Computer Science vol. 11657, pp. 304–318, 2019
[c33]Nobile M.S., Vlachou T., Spolaor S., Cazzaniga P., Mauri G., Pelicci P.G., Besozzi D.: ProCell: Investigating cell proliferation with Swarm Intelligence, 16th IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2019), Certosa di Pontignano, Siena, Tuscany, Italy, 2019
[c32]Nobile M.S., Cazzaniga P., Ashlock D.: Dilation functions in Global Optimization, IEEE Congress on Evolutionary Computation (CEC 2019), Wellington, New Zealand, 2019
[c31]Fuchs C., Spolaor S., Nobile M.S., Kaymak U.: A Swarm Intelligence approach to avoid local optima in Fuzzy C-Means clustering, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2019), New Orleans, LA, USA 2019
[c30]Tangherloni A., Spolaor S., Rundo L., Nobile M.S., Cazzaniga P., Mauri G., Liò P., Besozzi D., Merelli I.: GenHap: evolutionary computation for genotype assembly, 15th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics (CIBB 2018), Lisbon, Portugal, 2018
[c29]Totis N., Tangherloni A., Beccuti M., Cazzaniga P., Nobile M.S., Besozzi D., Pennisi M., Pappalardo F.: GPU powered parameter estimation of a large-scale kinetic metabolic network, 15th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics (CIBB 2018), Lisbon, Portugal, 2018
[c28]Damiani C., Pescini D., Nobile M.S.: Global sensitivity analysis of constraint-based metabolic models, 15th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics (CIBB 2018), Lecture Notes in Computer Science vol. 11925, Lisbon, Portugal, 2018
[c27]Tangherloni A., Rundo L., Spolaor S., Nobile M.S., Merelli I., Besozzi D., Mauri G., Cazzaniga P., Lio P.: High Performance Computing for Haplotyping: Models and Platforms, 24th International European Conference on Parallel and Distributed Computing (Euro-Par 2018), Lecture Notes on Computer Science vol. 11339, pp. 650–661, 2018
[c26]Beccuti M., Cazzaniga P., Pennisi M., Besozzi D., Nobile M.S., Pernice S., Russo G., Tangherloni A., Pappalardo F.: GPU accelerated analysis of Treg-Teff cross regulation in relapsing-remitting multiple sclerosis, 24th International European Conference on Parallel and Distributed Computing (Euro-Par 2018), Lecture Notes on Computer Science vol. 11339, pp. 626–637, 2018
[c25]Tangherloni A., Rundo L., Spolaor S., Cazzaniga P., and Nobile M.S.: GPU-powered multi-swarm parameter estimation of biological systems: a master-slave approach, Proceedings of the 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP2018), Cambridge (United Kingdom), 2018
[c24]Rundo L., Han C., Zhang J., Hataya R., Nagano Y., Militello C., Ferretti C., Nobile M.S., Tangherloni A., Gilardi M. C., Vitabile S., Nakayama H., Mauri G.: CNN-based prostate zonal segmentation on T2-weighted MR images: a cross-dataset study, Italian Workshop on Neural Networks (WIRN 2018), Vietri sul Mare (Italy), In: Esposito A., Faundez-Zanuy M., Morabito F., Pasero E. (eds) Neural Approaches to Dynamics of Signal Exchanges. Smart Innovation, Systems and Technologies, vol 151, pp. 269–280, Springer, Singapore, 2020
[c23]Ramazzotti D., Nobile M.S., Antoniotti M., Graudenzi A.: Structural learning of probabilistic graphical models of cumulative phenomena, Proceedings of the 18th International Conference on Computational Science (ICCS 2018), Wuxi (China), pp. 678–693, 2018
[c22]Nobile M.S., Tangherloni A., Rundo L., Spolaor S., Besozzi D., Mauri G., Cazzaniga P.: Computational Intelligence for Parameter Estimation of Biochemical Systems, Proceedings of IEEE World Congress on Computational Intelligence (WCCI 2018), Rio de Janeiro (Brasil), 2018
[c21]Spolaor S., Tangherloni A., Rundo L., Nobile M.S., Cazzaniga P.: Reboot strategies in Particle Swarm Optimization and their impact on parameter estimation of biochemical systems, Proceedings of the IEEE International Conference on Computational Intelligence and Bioinformatics (CIBCB 2017), Manchester (United Kingdom), 2017
[c20]Nobile M.S., Mauri G.: Accelerated analysis of biological parameters space using GPUs, 14th International Conference on Parallel Computing Technologies (PaCT 2017), Lecture Notes in Computer Science vol. 10421, Nizhni Novgorod (Russia), 2017
[c19]Tangherloni A., Rundo L., Nobile M.S.: Proactive Particles in Swarm Optimization: a settings-free algorithm for real-parameter single objective optimization problems, Proceedings of the 2017 IEEE Congress on Evolutionary Computation (CEC 2017), Donostia S. Sebastian (Spain), 2017
[c18]Spolaor S., Tangherloni A., Rundo L., Cazzaniga P., Nobile M.S.: Estimation of Kinetic Reaction Constants: Exploiting Reboot Strategies to Improve PSO’s Performance, Proceedings of the 14th International Computational Intelligence methods for Bioinformatics and Biostatistics, Cagliari (Italy), Lecture Notes on Computer Science 10834, 92:102, 2019
[c17]Tangherloni A., Nobile M.S., Cazzaniga P.: GPU-powered Bat Algorithm for the parameter estimation of biochemical kinetic values, Proceedings of the IEEE Conference on Computational Intelligence for Bioinformatics and Computational Biology (CIBCB 2016), Chiang Mai (Thailand), 2016
[c16]Ramazzotti D., Nobile M.S., Cazzaniga P., Mauri G., Antoniotti M.: Parallel implementation of efficient search schemes for the inference of cancer progression models, Proceedings of the IEEE Conference on Computational Intelligence for Bioinformatics and Computational Biology (CIBCB 2016), Chiang Mai (Thailand), 2016
[c15]Cumbo F., Nobile M.S., Damiani C., Colombo R., Mauri G., Cazzaniga P.: COSYS: A Computational Infrastructure for Systems Biology, Proceedings of the 13th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics (CIBB 2016), Lecture Notes in Computer Science vol. 10477, pp. 82–92, Stirling (United Kingdom), 2017
[c14]Nobile M.S., Tangherloni A., Besozzi D., Cazzaniga P.: GPU-powered and settings-free parameter estimation of biochemical systems, Proceedings of the 2016 IEEE Congress on Evolutionary Computation (CEC 2016), Vancouver (Canada), 2016
[c13]Nobile M.S., Iba H.: A double swarm methodology for parameter estimation in oscillating gene regulatory networks, Proceedings of the 2015 IEEE Congress on Evolutionary Computation (CEC 2015). S. Obayashi, C. Poloni, T. Murata (Eds.). Sendai (Japan), pp. 2376–2383, 2015
[c12]Nobile M.S., Pasi G., Cazzaniga P., Besozzi D., Colombo R., Mauri G.: Proactive Particles in Swarm Optimization: a self-tuning algorithm based on fuzzy logic, Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2015), Istanbul (Turkey), pp. 1–8, 2015
[c11]Cazzaniga P., Nobile M.S., Besozzi D.: The impact of particles initialization in PSO: parameter estimation as a case in point, Proceedings of the 2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2015), August 12-15, Niagara Falls (Canada), pp. 1–8, 2015
[c10]Tangherloni A., Cazzaniga P., Nobile M.S., Besozzi D., Mauri G.: Deterministic simulations of large-scale models of cellular processes accelerated on graphics processing units, Proceedings of the 12th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2015), Naples (Italy), 2015
[c9]Cazzaniga P., Ferrara F., Nobile M.S., Besozzi D., Mauri G.: Parallelizing biochemical stochastic simulations: a comparison of GPUs and Intel Xeon Phi coprocessors, Proceedings of the 13th International Conference on Parallel Computing Technologies (PaCT 2015), Petrozavodsk (Russia). V. Malyshkin (Ed.). Lecture Notes in Computer Science. Vol. 9251, pp. 363–374, 2015
[c8]Besozzi D., Nobile M.S., Cazzaniga P., Cipolla D., Mauri G.: From the inference of molecular structures to the analysis of emergent cellular dynamics: accelerating the computational study of biological systems with GPUs, Proceedings of the NETTAB 2014 Workshop: from Structural Bioinformatics to Integrative Systems Biology, Torino (Italy), pp. 88–90, 2014
[c7]Nobile M.S., Citrolo A.G., Cazzaniga P., Besozzi D., Mauri G.: A memetic hybrid method for the molecular distance geometry problem with incomplete information, Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC 2014), Beijing (China), pp. 1014–1021, 2014
[c6]Nobile M.S., Besozzi D., Cazzaniga P., Mauri G., Pescini D.: Reverse engineering of kinetic reaction networks by means of Cartesian Genetic Programming and Particle Swarm Optimization, Proceedings of the 2013 IEEE Conference on Evolutionary Computation (CEC 2013), Cancun (Mexico), Vol. 1, pp. 1594–1601, 2013
[c5]Nobile M.S.: Evolutionary inference of biochemical interaction networks accelerated on Graphics Processing Units, Proceedings of the 11th International Conference on High Performance Computing & Simulation 2013 (HPCS 2013), Helsinki (Finland), pp. 668–670, 2013
[c4]Nobile M.S., Besozzi D., Cazzaniga P., Mauri G.: The foundation of Evolutionary Petri Nets, Proceedings of the 4th International Workshop on Biological Processes & Petri Nets (BioPPN 2013), a satellite event of PETRI NETS 2013 (G. Balbo and M. Heiner, eds.), Milano (Italy), CEUR Workshop Proceedings, Vol. 988, pp. 60–74, 2013
[c3]Besozzi D., Caravagna G., Cazzaniga P., Nobile M. S., Pescini D., Re A.: GPU-powered simulation methodologies for biological systems, Wivace 2013 Italian Workshop on Artificial Life and Evolutionary Computation, A. Graudenzi, G. Caravagna, G. Mauri, M. Antoniotti (Eds.), EPTCS 130, Milano (Italy), 2013, pp. 87–91
[c2]Nobile M.S., Besozzi D., Cazzaniga P., Mauri G., Pescini D.: Estimating reaction constants in stochastic biological systems with a multi-swarm PSO running on GPUs, Proceedings of the fourteenth International Conference on Genetic and Evolutionary Computation Conference Companion. ACM New York, NY (USA) GECCO Companion ’12, pp. 1421–1422, 2012
[c1]Nobile M.S., Besozzi D., Cazzaniga P., Mauri G., Pescini D.: A GPU-based multi-swarm PSO method for parameter estimation in stochastic biological systems exploiting discrete-time target series, In 10th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Computational Biology, EvoBIO 2012, Malaga (Spain), Proceedings. M. Giacobini, L. Vanneschi, and W. Bush (Ed.). Lecture Notes in Computer Science. Vol. 7264, pp. 74–85, 2012
Vlachou T., Nobile M.S., Ronchini C., Besozzi D., Pelicci P.G.: An experimental and computational protocol to study cell proliferation in human Acute Myeloid Leukemia xenografts. In “Acute Myeloid Leukemia”. C. Cobaleda Hernandez and I. Sanchez-Garcia (editors). Part of Springer Nature’s “Methods in Molecular Biology” lab protocol series, volume 2185, 2020
Spolaor S., Gribaudo M., Iacono M., Kadavy T., Komínková Oplatková Z., Mauri G., Pllana S., Senkerik R., Stojanovic N., Turunen E., Viktorin A., Vitabile S., Zamuda A., Nobile M.S.: Towards Human Cell Simulation. In “cHiPSEt – High Performance Modeling and Simulation for Big Data Applications”. J. Kołodziej and H. González-Vélez (editors). Lecture Notes in Computer Science 11400. Springer. Pages 1–29, 2019 (in press)
Cazzaniga P., Nobile M.S., Tangherloni A., Besozzi D.: Accelerating stochastic simulations of mechanistic models of biological systems: Advantages and issues in the parallelization on Graphics Processing Units. In “Quantitative Biology: Computational Methods and Examples”. Brian Munsky, William Hlavacek, Lev Tsimring (editors). The MIT press. Pages 423–440, 2018
Nobile M.S., Cipolla D., Cazzaniga P., Besozzi D.: GPU-powered evolutionary design of mass-action based models of gene regulation. In “Evolutionary Computation in Gene Regulatory Network Research”, 1st edition. Hitoshi Iba, Nasimul Noman (editors). John Wiley & Sons. Pages 118–150, 2016
(Recent) abstracts and posters
Torlasco C., Papetti D., Sabatini M., Muscogiuri G., Castelletti S., Xue H., Kellman P., Parati G., Badano L.P., Nobile M.S., Besozzi D.: Techniques of Artificial Intelligence for the determination of the optimal inversion time: the THAITI project. European Heart Journal Supplements, Vol. 24, Issue Supplement_K, 2022
Torlasco C., Papetti D., Mene R., Artico J., Seraphim A., Badano L.P., Moon J.C., Parati G., Xue H., Kellman P., Nobile M.S.: Dark blood ischemic LGE segmentation using a deep learning approach. EuroCMR 2021
Nobile M.S., Vlachou T., Spolaor S., Bossi D., Cazzaniga P., Lanfrancone L., Besozzi D., Pelicci P.G., Mauri G.: A cell proliferation model of human acute myeloid leukemia xenograft. ISMB 2018, July 2018, Chicago, IL, USA
Besozzi D., Nobile M.S., Cazzaniga P., Spolaor S., Mauri G.: Dealing with cellular heterogeneity and lack of quantitative parameters in dynamical modeling of biological systems: a fuzzy logic based approach. CSHL Meeting “Cellular Dynamics & Models”, April 2017, New York, USA