A GPU-Based Multi-swarm PSO Method for Parameter Estimation in Stochastic Biological Systems Exploiting Discrete-Time Target Series. - Marco S. Nobile; Daniela Besozzi; Paolo Cazzaniga; Giancarlo Mauri; Dario Pescini (EvoBIO, 2012)

Estimating reaction constants in stochastic biological systems with a multi-swarm PSO running on GPUs. - Marco S. Nobile; Daniela Besozzi; Paolo Cazzaniga; Giancarlo Mauri; Dario Pescini (GECCO (Companion), 2012)

The foundation of Evolutionary Petri Nets. - Marco S. Nobile; Daniela Besozzi; Paolo Cazzaniga; Giancarlo Mauri (BioPPN@Petri Nets, 2013)

Reverse engineering of kinetic reaction networks by means of Cartesian Genetic Programming and Particle Swarm Optimization. - Marco S. Nobile; Daniela Besozzi; Paolo Cazzaniga; Dario Pescini; Giancarlo Mauri (IEEE Congress on Evolutionary Computation, 2013)

Evolutionary inference of biochemical reaction networks accelerated on graphics processing units. - Marco S. Nobile; Giancarlo Mauri (HPCS, 2013)

cupSODA: A CUDA-Powered Simulator of Mass-Action Kinetics. - Marco S. Nobile; Daniela Besozzi; Paolo Cazzaniga; Giancarlo Mauri; Dario Pescini (PaCT, 2013)

GPU-powered Simulation Methodologies for Biological Systems. - Daniela Besozzi; Giulio Caravagna; Paolo Cazzaniga; Marco S. Nobile; Dario Pescini; Alessandro Re (WIVACE, 2013)

A memetic hybrid method for the Molecular Distance Geometry Problem with incomplete information. - Marco S. Nobile; Andrea G. Citrolo; Paolo Cazzaniga; Daniela Besozzi; Giancarlo Mauri (IEEE Congress on Evolutionary Computation, 2014)

Simulation and Analysis of the Blood Coagulation Cascade Accelerated on GPU. - Matteo Bellini; Daniela Besozzi; Paolo Cazzaniga; Giancarlo Mauri; Marco S. Nobile (PDP, 2014)

GPU-accelerated simulations of mass-action kinetics models with cupSODA. - Marco S. Nobile; Paolo Cazzaniga; Daniela Besozzi; Giancarlo Mauri (J. Supercomput., 2014)

A double swarm methodology for parameter estimation in oscillating Gene Regulatory Networks. - Marco S. Nobile; Hitoshi Iba (CEC, 2015)

The impact of particles initialization in PSO: Parameter estimation as a case in point. - Paolo Cazzaniga; Marco S. Nobile; Daniela Besozzi (CIBCB, 2015)

Proactive Particles in Swarm Optimization: A self-tuning algorithm based on Fuzzy Logic. - Marco S. Nobile; Gabriella Pasi; Paolo Cazzaniga; Daniela Besozzi; Riccardo Colombo; Giancarlo Mauri (FUZZ-IEEE, 2015)

Parallelizing Biochemical Stochastic Simulations: A Comparison of GPUs and Intel Xeon Phi Processors. - Paolo Cazzaniga; F. Ferrara; Marco S. Nobile; Daniela Besozzi; Giancarlo Mauri (PaCT, 2015)

GPU-powered and settings-free parameter estimation of biochemical systems. - Marco S. Nobile; Andrea Tangherloni; Daniela Besozzi; Paolo Cazzaniga (CEC, 2016)

COSYS: A Computational Infrastructure for Systems Biology. - Fabio Cumbo; Marco S. Nobile; Chiara Damiani; Riccardo Colombo; Giancarlo Mauri; Paolo Cazzaniga (CIBB, 2016)

Parallel implementation of efficient search schemes for the inference of cancer progression models. - Daniele Ramazzotti; Marco S. Nobile; Paolo Cazzaniga; Giancarlo Mauri; Marco Antoniotti (CIBCB, 2016)

GPU-powered Bat Algorithm for the parameter estimation of biochemical kinetic values. - Andrea Tangherloni; Marco S. Nobile; Paolo Cazzaniga (CIBCB, 2016)

Proactive Particles in Swarm Optimization: A settings-free algorithm for real-parameter single objective optimization problems. - Andrea Tangherloni; Leonardo Rundo; Marco S. Nobile (CEC, 2017)

Estimation of Kinetic Reaction Constants: Exploiting Reboot Strategies to Improve PSO's Performance. - Simone Spolaor; Andrea Tangherloni; Leonardo Rundo; Paolo Cazzaniga; Marco S. Nobile (CIBB, 2017)

Reboot strategies in particle swarm optimization and their impact on parameter estimation of biochemical systems. - Simone Spolaor; Andrea Tangherloni; Leonardo Rundo; Marco S. Nobile; Paolo Cazzaniga (CIBCB, 2017)

Accelerated Analysis of Biological Parameters Space Using GPUs. - Marco S. Nobile; Giancarlo Mauri (PaCT, 2017)

Graphics processing units in bioinformatics, computational biology and systems biology. - Marco S. Nobile; Paolo Cazzaniga; Andrea Tangherloni; Daniela Besozzi (Briefings Bioinform., 2017)

GPU-powered model analysis with PySB/cupSODA. - Leonard A. Harris; Marco S. Nobile; James C. Pino; Alexander L. R. Lubbock; Daniela Besozzi; Giancarlo Mauri; Paolo Cazzaniga; Carlos F. Lopez (Bioinform., 2017)

LASSIE: simulating large-scale models of biochemical systems on GPUs. - Andrea Tangherloni; Marco S. Nobile; Daniela Besozzi; Giancarlo Mauri; Paolo Cazzaniga (BMC Bioinform., 2017)

Learning the Probabilistic Structure of Cumulative Phenomena with Suppes-Bayes Causal Networks. - Daniele Ramazzotti; Marco S. Nobile; Marco Antoniotti; Alex Graudenzi (CoRR, 2017)

Efficient Simulation of Reaction Systems on Graphics Processing Units. - Marco S. Nobile; Antonio E. Porreca; Simone Spolaor; Luca Manzoni; Paolo Cazzaniga; Giancarlo Mauri; Daniela Besozzi (Fundam. Informaticae, 2017)

Gillespie's Stochastic Simulation Algorithm on MIC coprocessors. - Andrea Tangherloni; Marco S. Nobile; Paolo Cazzaniga; Daniela Besozzi; Giancarlo Mauri (J. Supercomput., 2017)

Computational Intelligence for Parameter Estimation of Biochemical Systems. - Marco S. Nobile; Andrea Tangherloni; Leonardo Rundo; Simone Spolaor; Daniela Besozzi; Giancarlo Mauri; Paolo Cazzaniga (CEC, 2018)

Global Sensitivity Analysis of Constraint-Based Metabolic Models. - Chiara Damiani; Dario Pescini; Marco S. Nobile (CIBB, 2018)

Efficient and Settings-Free Calibration of Detailed Kinetic Metabolic Models with Enzyme Isoforms Characterization. - Niccoló Totis; Andrea Tangherloni; Marco Beccuti; Paolo Cazzaniga; Marco S. Nobile; Daniela Besozzi; Marzio Pennisi; Francesco Pappalardo 001 (CIBB, 2018)

GPU Accelerated Analysis of Treg-Teff Cross Regulation in Relapsing-Remitting Multiple Sclerosis. - Marco Beccuti; Paolo Cazzaniga; Marzio Pennisi; Daniela Besozzi; Marco S. Nobile; Simone Pernice; Giulia Russo; Andrea Tangherloni; Francesco Pappalardo 001 (Euro-Par Workshops, 2018)

High Performance Computing for Haplotyping: Models and Platforms. - Andrea Tangherloni; Leonardo Rundo; Simone Spolaor; Marco S. Nobile; Ivan Merelli; Daniela Besozzi; Giancarlo Mauri; Paolo Cazzaniga; Pietro Liò (Euro-Par Workshops, 2018)

Structural Learning of Probabilistic Graphical Models of Cumulative Phenomena. - Daniele Ramazzotti; Marco S. Nobile; Marco Antoniotti; Alex Graudenzi (ICCS (1), 2018)

GPU-Powered Multi-Swarm Parameter Estimation of Biological Systems: A Master-Slave Approach. - Andrea Tangherloni; Leonardo Rundo; Simone Spolaor; Paolo Cazzaniga; Marco S. Nobile (PDP, 2018)

Multi-objective optimization to explicitly account for model complexity when learning Bayesian Networks. - Paolo Cazzaniga; Marco S. Nobile; Daniele Ramazzotti (CoRR, 2018)

Fuzzy Self-Tuning PSO: A settings-free algorithm for global optimization. - Marco S. Nobile; Paolo Cazzaniga; Daniela Besozzi; Riccardo Colombo; Giancarlo Mauri; Gabriella Pasi (Swarm Evol. Comput., 2018)

Dilation Functions in Global Optimization. - Marco S. Nobile; Paolo Cazzaniga; Daniel A. Ashlock (CEC, 2019)

ProCell: Investigating cell proliferation with Swarm Intelligence. - Marco S. Nobile; Thalia Vlachou; Simone Spolaor; Paolo Cazzaniga; Giancarlo Mauri; Pier Giuseppe Pelicci; Daniela Besozzi (CIBCB, 2019)

A Swarm Intelligence Approach to Avoid Local Optima in Fuzzy C-Means Clustering. - Caro Fuchs; Simone Spolaor; Marco S. Nobile; Uzay Kaymak (FUZZ-IEEE, 2019)

HaraliCU: GPU-Powered Haralick Feature Extraction on Medical Images Exploiting the Full Dynamics of Gray-Scale Levels. - Leonardo Rundo; Andrea Tangherloni; Simone Galimberti; Paolo Cazzaniga; Ramona Woitek; Evis Sala; Marco S. Nobile; Giancarlo Mauri (PaCT, 2019)

A Novel Multi-objective Approach to Fuzzy Clustering. - Simone Spolaor; Caro Fuchs; Uzay Kaymak; Marco S. Nobile (SSCI, 2019)

Biochemical parameter estimation vs. benchmark functions: A comparative study of optimization performance and representation design. - Andrea Tangherloni; Simone Spolaor; Paolo Cazzaniga; Daniela Besozzi; Leonardo Rundo; Giancarlo Mauri; Marco S. Nobile (Appl. Soft Comput., 2019)

Modeling cell proliferation in human acute myeloid leukemia xenografts. - Marco S. Nobile; Thalia Vlachou; Simone Spolaor; Daniela Bossi; Paolo Cazzaniga; Luisa Lanfrancone; Giancarlo Mauri; Pier Giuseppe Pelicci; Daniela Besozzi (Bioinform., 2019)

GenHap: a novel computational method based on genetic algorithms for haplotype assembly. - Andrea Tangherloni; Simone Spolaor; Leonardo Rundo; Marco S. Nobile; Paolo Cazzaniga; Giancarlo Mauri; Pietro Liò; Ivan Merelli; Daniela Besozzi (BMC Bioinform., 2019)

A novel framework for MR image segmentation and quantification by using MedGA. - Leonardo Rundo; Andrea Tangherloni; Paolo Cazzaniga; Marco S. Nobile; Giorgio Russo; Maria Carla Gilardi; Salvatore Vitabile; Giancarlo Mauri; Daniela Besozzi; Carmelo Militello (Comput. Methods Programs Biomed., 2019)

CNN-based Prostate Zonal Segmentation on T2-weighted MR Images: A Cross-dataset Study. - Leonardo Rundo; Changhee Han; Jin Zhang; Ryuichiro Hataya; Yudai Nagano; Carmelo Militello; Claudio Ferretti; Marco S. Nobile; Andrea Tangherloni; Maria Carla Gilardi; Salvatore Vitabile; Hideki Nakayama; et al. (CoRR, 2019)

MedGA: A novel evolutionary method for image enhancement in medical imaging systems. - Leonardo Rundo; Andrea Tangherloni; Marco S. Nobile; Carmelo Militello; Daniela Besozzi; Giancarlo Mauri; Paolo Cazzaniga (Expert Syst. Appl., 2019)

USE-Net: Incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets. - Leonardo Rundo; Changhee Han; Yudai Nagano; Jin Zhang; Ryuichiro Hataya; Carmelo Militello; Andrea Tangherloni; Marco S. Nobile; Claudio Ferretti; Daniela Besozzi; Maria Carla Gilardi; Salvatore Vitabile; et al. (Neurocomputing, 2019)

Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena. - Daniele Ramazzotti; Marco S. Nobile; Marco Antoniotti; Alex Graudenzi (J. Comput. Sci., 2019)

ginSODA: massive parallel integration of stiff ODE systems on GPUs. - Marco S. Nobile; Paolo Cazzaniga; Daniela Besozzi; Giancarlo Mauri (J. Supercomput., 2019)

Towards Human Cell Simulation. - Simone Spolaor; Marco Gribaudo; Mauro Iacono; Tomas Kadavy; Zuzana Komínková Oplatková; Giancarlo Mauri; Sabri Pllana; Roman Senkerik; Natalija Stojanovic; Esko Turunen; Adam Viktorin; Salvatore Vitabile; et al. (High-Performance Modelling and Simulation for Big Data Applications, 2019)

Preventing litigation with a predictive model of COVID-19 ICUs occupancy. - Chiara Gallese; Elena Falletti; Marco S. Nobile; Lucrezia Ferrario; Fabrizio Schettini; Emanuela Foglia (IEEE BigData, 2020)

Which random is the best random? A study on sampling methods in Fourier surrogate modeling. - Marco S. Nobile; Simone Spolaor; Paolo Cazzaniga; Daniele M. Papetti; Daniela Besozzi; Daniel A. Ashlock; Luca Manzoni (CEC, 2020)

Fourier Surrogate Models of Dilated Fitness Landscapes in Systems Biology : or how we learned to torture optimization problems until they confess. - Marco S. Nobile; Paolo Cazzaniga; Simone Spolaor; Daniela Besozzi; Luca Manzoni (CIBCB, 2020)

pyFUME: a Python Package for Fuzzy Model Estimation. - Caro Fuchs; Simone Spolaor; Marco S. Nobile; Uzay Kaymak (FUZZ-IEEE, 2020)

On the automatic calibration of fully analogical spiking neuromorphic chips. - Daniele M. Papetti; Simone Spolaor; Daniela Besozzi; Paolo Cazzaniga; Marco Antoniotti; Marco S. Nobile (IJCNN, 2020)

A Graph Theory Approach to Fuzzy Rule Base Simplification. - Caro Fuchs; Simone Spolaor; Marco S. Nobile; Uzay Kaymak (IPMU (1), 2020)

Fuzzy modeling and global optimization to predict novel therapeutic targets in cancer cells. - Marco S. Nobile; Giuseppina Votta; Roberta Palorini; Simone Spolaor; Humberto De Vitto; Paolo Cazzaniga; Francesca Ricciardiello; Giancarlo Mauri; Lilia Alberghina; Ferdinando Chiaradonna; Daniela Besozzi (Bioinform., 2020)

Surfing on Fitness Landscapes: A Boost on Optimization by Fourier Surrogate Modeling. - Luca Manzoni; Daniele M. Papetti; Paolo Cazzaniga; Simone Spolaor; Giancarlo Mauri; Daniela Besozzi; Marco S. Nobile (Entropy, 2020)

Computational Intelligence for Life Sciences. - Daniela Besozzi; Luca Manzoni; Marco S. Nobile; Simone Spolaor; Mauro Castelli; Leonardo Vanneschi; Paolo Cazzaniga; Stefano Ruberto; Leonardo Rundo; Andrea Tangherloni (Fundam. Informaticae, 2020)

Simpful: A User-Friendly Python Library for Fuzzy Logic. - Simone Spolaor; Caro Fuchs; Paolo Cazzaniga; Uzay Kaymak; Daniela Besozzi; Marco S. Nobile (Int. J. Comput. Intell. Syst., 2020)

Coupling Mechanistic Approaches and Fuzzy Logic to Model and Simulate Complex Systems. - Simone Spolaor; Marco S. Nobile; Giancarlo Mauri; Paolo Cazzaniga; Daniela Besozzi (IEEE Trans. Fuzzy Syst., 2020)

cuProCell: GPU-Accelerated Analysis of Cell Proliferation With Flow Cytometry Data. - Marco S. Nobile; Eric Nisoli; Thalia Vlachou; Simone Spolaor; Paolo Cazzaniga; Giancarlo Mauri; Pier Giuseppe Pelicci; Daniela Besozzi (IEEE J. Biomed. Health Informatics, 2020)

CNN-Based Prostate Zonal Segmentation on T2-Weighted MR Images: A Cross-Dataset Study. - Leonardo Rundo; Changhee Han; Jin Zhang; Ryuichiro Hataya; Yudai Nagano; Carmelo Militello; Claudio Ferretti; Marco S. Nobile; Andrea Tangherloni; Maria Carla Gilardi; Salvatore Vitabile; Hideki Nakayama; et al. (Neural Approaches to Dynamics of Signal Exchanges, 2020)

If You Can't Beat It, Squash It: Simplify Global Optimization by Evolving Dilation Functions. - Daniele M. Papetti; Daniel A. Ashlock; Paolo Cazzaniga; Daniela Besozzi; Marco S. Nobile (CEC, 2021)

The Impact of Representation on the Optimization of Marker Panels for Single-cell RNA Data. - Andrea Tangherloni; Simone G. Riva; Simone Spolaor; Daniela Besozzi; Marco S. Nobile; Paolo Cazzaniga (CEC, 2021)

A comparison of multi-objective optimization algorithms to identify drug target combinations. - Simone Spolaor; Daniele M. Papetti; Paolo Cazzaniga; Daniela Besozzi; Marco S. Nobile (CIBCB, 2021)

Characterizing the flying behaviour of bird flocks with fuzzy reasoning. - Elisa Perinot; Johannes Fritz; Leonida Fusani; Bernhard Voelkl; Marco S. Nobile (WILF, 2021)

Tremor assessment using smartphone sensor data and fuzzy reasoning. - Caro Fuchs; Marco S. Nobile; Guillaume Zamora; Aurélie Degeneffe; Pieter Leonard Kubben; Uzay Kaymak (BMC Bioinform., 2021)

Accelerated global sensitivity analysis of genome-wide constraint-based metabolic models. - Marco S. Nobile; Vasco Coelho; Dario Pescini; Chiara Damiani (BMC Bioinform., 2021)

Investigating the performance of multi-objective optimization when learning Bayesian Networks. - Marco S. Nobile; Paolo Cazzaniga; Daniele Ramazzotti (Neurocomputing, 2021)

FiCoS: A fine-grained and coarse-grained GPU-powered deterministic simulator for biochemical networks. - Andrea Tangherloni; Marco S. Nobile; Paolo Cazzaniga; Giulia Capitoli; Simone Spolaor; Leonardo Rundo; Giancarlo Mauri; Daniela Besozzi (PLoS Comput. Biol., 2021)

A CUDA-powered method for the feature extraction and unsupervised analysis of medical images. - Leonardo Rundo; Andrea Tangherloni; Paolo Cazzaniga; Matteo Mistri; Simone Galimberti; Ramona Woitek; Evis Sala; Giancarlo Mauri; Marco S. Nobile (J. Supercomput., 2021)

The Impact of Variable Selection and Transformation on the Interpretability and Accuracy of Fuzzy Models. - Caro Fuchs; Simone Spolaor; Uzay Kaymak; Marco S. Nobile (CIBCB, 2022)

Predicting and Characterizing Legal Claims of Hospitals with Computational Intelligence: the Legal and Ethical Implications. - Chiara Gallese; Caro Fuchs; Simone G. Riva; Emanuela Foglia; Fabrizio Schettini; Lucrezia Ferrario; Elena Falletti; Marco S. Nobile (CIBCB, 2022)

Comparing Interpretable AI Approaches for the Clinical Environment: an Application to COVID-19. - Mohsen Abbaspour Onari; Marco S. Nobile; Isel Grau; Caro Fuchs; Yingqian Zhang 001; Arjen-Kars Boer; Volkher Scharnhorst (CIBCB, 2022)

Local Bubble Dilation Functions: Hypersphere-bounded Landscape Deformations Simplify Global Optimization. - Daniele M. Papetti; Vasco Coelho; Daniel A. Ashlock; Paolo Cazzaniga; Simone Spolaor; Daniela Besozzi; Marco S. Nobile (CIBCB, 2022)

Building Interpretable and Parsimonious Fuzzy Models using a Multi-Objective Approach. - Caro Fuchs; Uzay Kaymak; Marco S. Nobile (FUZZ-IEEE, 2022)

Salp Swarm Optimization: A critical review. - Mauro Castelli; Luca Manzoni; Luca Mariot; Marco S. Nobile; Andrea Tangherloni (Expert Syst. Appl., 2022)

SMGen: A Generator of Synthetic Models of Biochemical Reaction Networks. - Simone G. Riva; Paolo Cazzaniga; Marco S. Nobile; Simone Spolaor; Leonardo Rundo; Daniela Besozzi; Andrea Tangherloni (Symmetry, 2022)

Trustworthy Machine Learning Predictions to Support Clinical Research and Decisions. - Andrea Bianchi; Antinisca Di Marco; Francesca Marzi; Giovanni Stilo; Cristina Pellegrini; Stefano Masi; Alessandro Mengozzi; Agostino Virdis; Marco Salvatore Nobile; Marta Simeoni (CBMS, 2023)

The Domination Game: Dilating Bubbles to Fill Up Pareto Fronts. - Vasco Coelho; Daniele M. Papetti; Andrea Tangherloni; Paolo Cazzaniga; Daniela Besozzi; Marco S. Nobile (CEC, 2023)

Investigating Semi-Automatic Assessment of Data Sets Fairness by Means of Fuzzy Logic. - Chiara Gallese; Teresa Scantamburlo; Luca Manzoni; Marco S. Nobile (CIBCB, 2023)

Trustworthy Artificial Intelligence in Medical Applications: A Mini Survey. - Mohsen Abbaspour Onari; Isel Grau; Marco S. Nobile; Yingqian Zhang 001 (CIBCB, 2023)

Estimation of Fuzzy Models from Mixed Data Sets with pyFUME. - Daniele M. Papetti; Caro Fuchs; Vasco Coelho; Uzay Kaymak; Marco S. Nobile (CIBCB, 2023)

A Theoretical Framework for AI Models Explainability with Application in Biomedicine. - Matteo Rizzo; Alberto Veneri; Andrea Albarelli; Claudio Lucchese; Marco S. Nobile; Cristina Conati (CIBCB, 2023)

Assisting clinical practice with fuzzy probabilistic decision trees. - Emma L. Ambags; Giulia Capitoli; Vincenzo L' Imperio; Michele Provenzano; Marco S. Nobile; Pietro Liò (CoRR, 2023)

Measuring Perceived Trust in XAI-Assisted Decision-Making by Eliciting a Mental Model. - Mohsen Abbaspour Onari; Isel Grau; Marco S. Nobile; Yingqian Zhang 001 (CoRR, 2023)

Models of Representation in Computational Intelligence [Guest Editorial]. - Marco S. Nobile; Luca Manzoni; Daniel A. Ashlock; Rong Qu (IEEE Comput. Intell. Mag., 2023)

An accurate and time-efficient deep learning-based system for automated segmentation and reporting of cardiac magnetic resonance-detected ischemic scar. - Daniele M. Papetti; Kirsten van Abeelen; Rhodri H. Davies; Roberto Menè; Francesca Heilbron; Francesco P. Perelli; Jessica Artico; Andreas Seraphim; James C. Moon; Gianfranco Parati; Hui Xue 006; Peter Kellman; et al. (Comput. Methods Programs Biomed., 2023)

Unsupervised neural networks as a support tool for pathology diagnosis in MALDI-MSI experiments: A case study on thyroid biopsies. - Marco S. Nobile; Giulia Capitoli; Virgil Sowirono; Francesca Clerici; Isabella Piga; Kirsten van Abeelen; Fulvio Magni; Fabio Pagni; Stefania Galimberti; Paolo Cazzaniga; Daniela Besozzi (Expert Syst. Appl., 2023)

Barcode demultiplexing of nanopore sequencing raw signals by unsupervised machine learning. - Daniele M. Papetti; Simone Spolaor; Iman Nazari; Andrea Tirelli; Tommaso Leonardi; Chiara Caprioli; Daniela Besozzi; Thalia Vlachou; Pier Giuseppe Pelicci; Paolo Cazzaniga; Marco S. Nobile (Frontiers Bioinform., 2023)

Ten quick tips for fuzzy logic modeling of biomedical systems. - Davide Chicco; Simone Spolaor; Marco S. Nobile (PLoS Comput. Biol., 2023)

Predicting Metabolic Reactions with a Molecular Transformer for Drug Design Optimization. - Silvia Multari; Riza Özçelik; Angelica Mazzolari; Marco Salvatore Nobile; Francesca Grisoni (CIBCB, 2024)

A Fast Feature Selection for Interpretable Modeling Based on Fuzzy Inference Systems. - Andrea Tangherloni; Paolo Cazzaniga; Nicolò Stranieri; Francesca M. Buffa; Marco S. Nobile (CIBCB, 2024)

Applications of IFIS python library in interval-valued fuzzy inference problems. - Barbara Pékala; Piotr Grochowalski; Dawid Kosior; Dorota Gil; Wojciech Koziol; Krzysztof Dyczkowski; Uzay Kaymak; Caro Fuchs; Marco S. Nobile (FUZZ, 2024)

An explainable data-driven decision support framework for strategic customer development. - Mohsen Abbaspour Onari; Mustafa Jahangoshai Rezaee; Morteza Saberi; Marco S. Nobile (Knowl. Based Syst., 2024)

Python library for interval-valued fuzzy inference. - Krzysztof Dyczkowski; Piotr Grochowalski; Dawid Kosior; Dorota Gil; Wojciech Koziol; Barbara Pekala; Uzay Kaymak; Caro Fuchs; Marco S. Nobile (SoftwareX, 2024)

A Survey of Modern Hybrid Particle Swarm Optimization Algorithms. - Matteo Grazioso; Chiara Gallese; Leonardo Vanneschi; Marco S. Nobile (EvoApplications (2), 2025)

We Are Sending You Back... to the Optimum! Fuzzy Time Travel Particle Swarm Optimization. - Daniele M. Papetti; Andrea Tangherloni; Vasco Coelho; Daniela Besozzi; Paolo Cazzaniga; Marco S. Nobile (EvoApplications (2), 2025)

Multimodal Attention-Aware Fusion for Diagnosing Distal Myopathy: Evaluating Model Interpretability and Clinician Trust. - Mohsen Abbaspour Onari; Lucie Charlotte Magister; Yaoxin Wu; Amalia Lupi; Dario Creazzo; Mattia Tordin; Luigi Di Donatantonio; Emilio Quaia; Chao Zhang 071; Isel Grau; Marco S. Nobile; Yingqian Zhang 001; et al. (CoRR, 2025)