NEURObjects: A Set of Library Classes for Neural Networks Development. - Giorgio Valentini; Francesco Masulli (IIA/SOCO, 1999)

Parallel Non Linear Dichotomizers. - Francesco Masulli; Giorgio Valentini (IJCNN (2), 2000)

Comparing decomposition methods for classification. - Francesco Masulli; Giorgio Valentini (KES, 2000)

Effectiveness of Error Correcting Output Codes in Multiclass Learning Problems. - Francesco Masulli; Giorgio Valentini (Multiple Classifier Systems, 2000)

Dependence among Codeword Bits Errors in ECOC Learning Machines: An Experimental Analysis. - Francesco Masulli; Giorgio Valentini (Multiple Classifier Systems, 2001)

Boosting and Classification of Electronic Nose Data. - Francesco Masulli; Matteo Pardo; Giorgio Sberveglieri; Giorgio Valentini (Multiple Classifier Systems, 2002)

Bias-Variance Analysis and Ensembles of SVM. - Giorgio Valentini; Thomas G. Dietterich (Multiple Classifier Systems, 2002)

Ensembles of Learning Machines. - Giorgio Valentini; Francesco Masulli (WIRN, 2002)

Gene expression data analysis of human lymphoma using support vector machines and output coding ensembles. - Giorgio Valentini (Artif. Intell. Medicine, 2002)

NEURObjects: an object-oriented library for neural network development. - Giorgio Valentini; Francesco Masulli (Neurocomputing, 2002)

Low Bias Bagged Support Vector Machines. - Giorgio Valentini; Thomas G. Dietterich (ICML, 2003)

Bagged ensembles of Support Vector Machines for gene expression data analysis. - Giorgio Valentini; Marco Muselli; Francesca Ruffino (IJCNN, 2003)

An Application of Low Bias Bagged SVMs to the Classification of Heterogeneous Malignant Tissues. - Giorgio Valentini (WIRN, 2003)

Ensemble methods based on bias-variance analysis. - Giorgio Valentini (2003)

Random Aggregated and Bagged Ensembles of SVMs: An Empirical Bias?Variance Analysis. - Giorgio Valentini (Multiple Classifier Systems, 2004)

Feature Selection Combined with Random Subspace Ensemble for Gene Expression Based Diagnosis of Malignancies. - Alberto Bertoni; Raffaella Folgieri; Giorgio Valentini (WIRN, 2004)

An experimental analysis of the dependence among codeword bit errors in ECOC learning machines. - Francesco Masulli; Giorgio Valentini (Neurocomputing, 2004)

Cancer recognition with bagged ensembles of support vector machines. - Giorgio Valentini; Marco Muselli; Francesca Ruffino (Neurocomputing, 2004)

Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods. - Giorgio Valentini; Thomas G. Dietterich (J. Mach. Learn. Res., 2004)

Effectiveness of error correcting output coding methods in ensemble and monolithic learning machines. - Francesco Masulli; Giorgio Valentini (Pattern Anal. Appl., 2004)

Lung nodules detection and classification. - Paola Campadelli; Elena Casiraghi; Giorgio Valentini (ICIP (1), 2005)

Random projections for assessing gene expression cluster stability. - Alberto Bertoni; Giorgio Valentini (IJCNN, 2005)

Biological Specifications for a Synthetic Gene Expression Data Generation Model. - Francesca Ruffino; Marco Muselli; Giorgio Valentini (WILF, 2005)

Ensembles Based on Random Projections to Improve the Accuracy of Clustering Algorithms. - Alberto Bertoni; Giorgio Valentini (WIRN/NAIS, 2005)

Bio-molecular cancer prediction with random subspace ensembles of support vector machines. - Alberto Bertoni; Raffaella Folgieri; Giorgio Valentini (Neurocomputing, 2005)

Support vector machines for candidate nodules classification. - Paola Campadelli; Elena Casiraghi; Giorgio Valentini (Neurocomputing, 2005)

An experimental bias-variance analysis of SVM ensembles based on resampling techniques. - Giorgio Valentini (IEEE Trans. Syst. Man Cybern. Part B, 2005)

Randomized maps for assessing the reliability of patients clusters in DNA microarray data analyses. - Alberto Bertoni; Giorgio Valentini (Artif. Intell. Medicine, 2006)

Clusterv: a tool for assessing the reliability of clusters discovered in DNA microarray data. - Giorgio Valentini (Bioinform., 2006)

Characterization of lung tumor subtypes through gene expression cluster validity assessment. - Giorgio Valentini; Francesca Ruffino (RAIRO Theor. Informatics Appl., 2006)

Discovering Significant Structures in Clustered Bio-molecular Data Through the Bernstein Inequality. - Alberto Bertoni; Giorgio Valentini (KES (3), 2007)

Fuzzy Ensemble Clustering for DNA Microarray Data Analysis. - Roberto Avogadri; Giorgio Valentini (WILF, 2007)

Mosclust: a software library for discovering significant structures in bio-molecular data. - Giorgio Valentini (Bioinform., 2007)

Model order selection for bio-molecular data clustering. - Alberto Bertoni; Giorgio Valentini (BMC Bioinform., 2007)

Unsupervised Stability-Based Ensembles to Discover Reliable Structures in Complex Bio-molecular Data. - Alberto Bertoni; Giorgio Valentini (CIBB, 2008)

Dataset complexity can help to generate accurate ensembles of k-nearest neighbors. - Oleg Okun; Giorgio Valentini (IJCNN, 2008)

An Algorithm to Assess the Reliability of Hierarchical Clusters in Gene Expression Data. - Roberto Avogadri; Matteo Brioschi; Francesca Ruffino; Fulvia Ferrazzi; Alessandro Beghini; Giorgio Valentini (KES (3), 2008)

Classification of DNA microarray data with Random Projection Ensembles of Polynomial SVMs. - Alberto Bertoni; Raffaella Folgieri; Giorgio Valentini (WIRN, 2008)

HCGene: a software tool to support the hierarchical classification of genes. - Giorgio Valentini; Nicolò Cesa-Bianchi (Bioinform., 2008)

Discovering multi-level structures in bio-molecular data through the Bernstein inequality. - Alberto Bertoni; Giorgio Valentini (BMC Bioinform., 2008)

Gene expression modeling through positive boolean functions. - Francesca Ruffino; Marco Muselli; Giorgio Valentini (Int. J. Approx. Reason., 2008)

Ensemble Based Data Fusion for Gene Function Prediction. - Matteo Re; Giorgio Valentini (MCS, 2009)

True Path Rule Hierarchical Ensembles. - Giorgio Valentini (MCS, 2009)

Comparing early and late data fusion methods for gene function prediction. - Matteo Re; Giorgio Valentini (WIRN, 2009)

Fuzzy ensemble clustering based on random projections for DNA microarray data analysis. - Roberto Avogadri; Giorgio Valentini (Artif. Intell. Medicine, 2009)

Computational intelligence and machine learning in bioinformatics. - Giorgio Valentini; Roberto Tagliaferri; Francesco Masulli (Artif. Intell. Medicine, 2009)

XML-based approaches for the integration of heterogeneous bio-molecular data. - Marco Mesiti; Ernesto Jiménez-Ruiz; Ismael Sanz; Rafael Berlanga Llavori; Paolo Perlasca; Giorgio Valentini; David Manset (BMC Bioinform., 2009)

A stability-based algorithm to validate hierarchical clusters of genes. - Roberto Avogadri; Matteo Brioschi; Fulvia Ferrazzi; Matteo Re; Alessandro Beghini; Giorgio Valentini (Int. J. Knowl. Eng. Soft Data Paradigms, 2009)

Classification of co-expressed genes from DNA regulatory regions. - Giulio Pavesi; Giorgio Valentini (Inf. Fusion, 2009)

Prediction of Gene Function Using Ensembles of SVMs and Heterogeneous Data Sources. - Matteo Re; Giorgio Valentini (Applications of Supervised and Unsupervised Ensemble Methods, 2009)

An Experimental Comparison of Hierarchical Bayes and True Path Rule Ensembles for Protein Function Prediction. - Matteo Re; Giorgio Valentini (MCS, 2010)

Learning functional linkage networks with a cost-sensitive approach. - Alberto Bertoni; Marco Frasca 001; Giuliano Grossi; Giorgio Valentini (WIRN, 2010)

Dynamic multi-objective routing algorithm: a multi-objective routing algorithm for the simple hybrid routing protocol on wireless sensor networks. - Giorgio Valentini; Cláudia J. Barenco Abbas; L. Javier García-Villalba; Luis Astorga (IET Commun., 2010)

Integration of heterogeneous data sources for gene function prediction using decision templates and ensembles of learning machines. - Matteo Re; Giorgio Valentini (Neurocomputing, 2010)

Noise tolerance of Multiple Classifier Systems in data integration-based gene function prediction. - Matteo Re; Giorgio Valentini (J. Integr. Bioinform., 2010)

Hierarchical Cost-Sensitive Algorithms for Genome-Wide Gene Function Prediction. - Nicolò Cesa-Bianchi; Giorgio Valentini (MLSB, 2010)

Simple ensemble methods are competitive with state-of-the-art data integration methods for gene function prediction. - Matteo Ré; Giorgio Valentini (MLSB, 2010)

COSNet: A Cost Sensitive Neural Network for Semi-supervised Learning in Graphs. - Alberto Bertoni; Marco Frasca 001; Giorgio Valentini (ECML/PKDD (1), 2011)

Identification of promoter regions in genomic sequences by 1-dimensional constraint clustering. - Alberto Bertoni; Matteo Re; Francesco Saccà; Giorgio Valentini (WIRN, 2011)

A Mathematical Model for the Validation of Gene Selection Methods. - Marco Muselli; Alberto Bertoni; Marco Frasca 001; Alessandro Beghini; Francesca Ruffino; Giorgio Valentini (IEEE ACM Trans. Comput. Biol. Bioinform., 2011)

True Path Rule Hierarchical Ensembles for Genome-Wide Gene Function Prediction. - Giorgio Valentini (IEEE ACM Trans. Comput. Biol. Bioinform., 2011)

A Novel Ensemble Technique for Protein Subcellular Location Prediction. - Alessandro Rozza; Gabriele Lombardi; Matteo Re; Elena Casiraghi; Giorgio Valentini; Paola Campadelli (Ensembles in Machine Learning Applications, 2011)

Random Walking on Functional Interaction Networks to Rank Genes Involved in Cancer. - Matteo Re; Giorgio Valentini (AIAI (2), 2012)

Large Scale Ranking and Repositioning of Drugs with Respect to DrugBank Therapeutic Categories. - Matteo Re; Giorgio Valentini (ISBRA, 2012)

Cancer module genes ranking using kernelized score functions. - Matteo Re; Giorgio Valentini (BMC Bioinform., 2012)

Synergy of multi-label hierarchical ensembles, data fusion, and cost-sensitive methods for gene functional inference. - Nicolò Cesa-Bianchi; Matteo Re; Giorgio Valentini (Mach. Learn., 2012)

A Fast Ranking Algorithm for Predicting Gene Functions in Biomolecular Networks. - Matteo Re; Marco Mesiti; Giorgio Valentini (IEEE ACM Trans. Comput. Biol. Bioinform., 2012)

Optimisation of the enhanced distance based broadcasting protocol for MANETs. - Patricia Ruiz; Bernabé Dorronsoro; Giorgio Valentini; Frédéric Pinel; Pascal Bouvry (J. Supercomput., 2012)

An overview of energy efficiency techniques in cluster computing systems. - Giorgio Valentini; Walter Lassonde; Samee Ullah Khan; Nasro Min-Allah; Sajjad Ahmad Madani; Juan Li 004; Limin Zhang; Lizhe Wang 001; Nasir Ghani; Joanna Kolodziej; Hongxiang Li; Albert Y. Zomaya; et al. (Clust. Comput., 2013)

A neural network algorithm for semi-supervised node label learning from unbalanced data. - Marco Frasca 001; Alberto Bertoni; Matteo Re; Giorgio Valentini (Neural Networks, 2013)

Network-Based Drug Ranking and Repositioning with Respect to DrugBank Therapeutic Categories. - Matteo Re; Giorgio Valentini (IEEE ACM Trans. Comput. Biol. Bioinform., 2013)

A Novel Approach to the Problem of Non-uniqueness of the Solution in Hierarchical Clustering. - Isabella Cattinelli; Giorgio Valentini; Eraldo Paulesu; N. Alberto Borghese (IEEE Trans. Neural Networks Learn. Syst., 2013)

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods. - Giorgio Valentini; Alberto Paccanaro; Horacio Caniza; Alfonso E. Romero; Matteo Re (Artif. Intell. Medicine, 2014)

GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology. - Horacio Caniza; Alfonso E. Romero; Samuel Heron; Haixuan Yang; Alessandra Devoto; Marco Frasca 001; Marco Mesiti; Giorgio Valentini; Alberto Paccanaro (Bioinform., 2014)

Notes on hierarchical ensemble methods for DAG-structured taxonomies. - Giorgio Valentini (CoRR, 2014)

Prediction of Human Gene - Phenotype Associations by Exploiting the Hierarchical Structure of the Human Phenotype Ontology. - Giorgio Valentini; Sebastian Köhler 001; Matteo Ré; Marco Notaro; Peter N. Robinson (IWBBIO (1), 2015)

A Hierarchical Ensemble Method for DAG-Structured Taxonomies. - Peter N. Robinson; Marco Frasca 001; Sebastian Köhler 001; Marco Notaro; Matteo Re; Giorgio Valentini (MCS, 2015)

UNIPred: Unbalance-Aware Network Integration and Prediction of Protein Functions. - Marco Frasca 001; Alberto Bertoni; Giorgio Valentini (J. Comput. Biol., 2015)

Within network learning on big graphs using secondary memory-based random walk kernels. - Jianyi Lin; Marco Mesiti; Matteo Re; Giorgio Valentini (COMPLEX NETWORKS, 2016)

Multi-species protein function prediction: towards web-based visual analytics. - Paolo Perlasca; Giorgio Valentini; Marco Frasca 001; Marco Mesiti (iiWAS, 2016)

RANKS: a flexible tool for node label ranking and classification in biological networks. - Giorgio Valentini; Giuliano Armano; Marco Frasca 001; Jianyi Lin; Marco Mesiti; Matteo Re (Bioinform., 2016)

Learning node labels with multi-category Hopfield networks. - Marco Frasca 001; Simone Bassis; Giorgio Valentini (Neural Comput. Appl., 2016)

Disease-Genes Must Guide Data Source Integration in the Gene Prioritization Process. - Marco Frasca 001; Jean-Fred Fontaine; Giorgio Valentini; Marco Mesiti; Marco Notaro; Dario Malchiodi; Miguel A. Andrade-Navarro (CIBB, 2017)

Ensembling Descendant Term Classifiers to Improve Gene - Abnormal Phenotype Predictions. - Marco Notaro; Max Schubach; Marco Frasca 001; Marco Mesiti; Peter N. Robinson; Giorgio Valentini (CIBB, 2017)

Prediction of Human Phenotype Ontology terms by means of hierarchical ensemble methods. - Marco Notaro; Max Schubach; Peter N. Robinson; Giorgio Valentini (BMC Bioinform., 2017)

COSNet: An R package for label prediction in unbalanced biological networks. - Marco Frasca 001; Giorgio Valentini (Neurocomputing, 2017)

Committee-Based Active Learning to Select Negative Examples for Predicting Protein Functions. - Marco Frasca 001; Maryam Sepehri; Alessandro Petrini; Giuliano Grossi; Giorgio Valentini (CIBB, 2018)

A Graphical Tool for the Exploration and Visual Analysis of Biomolecular Networks. - Cheick Tidiane Ba; Elena Casiraghi; Marco Frasca 001; Jessica Gliozzo; Giuliano Grossi; Marco Mesiti; Marco Notaro; Paolo Perlasca; Alessandro Petrini; Matteo Re; Giorgio Valentini (CIBB, 2018)

A GPU-based algorithm for fast node label learning in large and unbalanced biomolecular networks. - Marco Frasca 001; Giuliano Grossi; Jessica Gliozzo; Marco Mesiti; Marco Notaro; Paolo Perlasca; Alessandro Petrini; Giorgio Valentini (BMC Bioinform., 2018)

On the Quality of Classification Models for Inferring ABAC Policies from Access Logs. - Luca Cappelletti; Stefano Valtolina; Giorgio Valentini; Marco Mesiti; Elisa Bertino (IEEE BigData, 2019)

Multitask Hopfield Networks. - Marco Frasca 001; Giuliano Grossi; Giorgio Valentini (ECML/PKDD (2), 2019)

UNIPred-Web: a web tool for the integration and visualization of biomolecular networks for protein function prediction. - Paolo Perlasca; Marco Frasca 001; Cheick Tidiane Ba; Marco Notaro; Alessandro Petrini; Elena Casiraghi; Giuliano Grossi; Jessica Gliozzo; Giorgio Valentini; Marco Mesiti (BMC Bioinform., 2019)

Bayesian Optimization Improves Tissue-Specific Prediction of Active Regulatory Regions with Deep Neural Networks. - Luca Cappelletti; Alessandro Petrini; Jessica Gliozzo; Elena Casiraghi; Max Schubach; Martin Kircher; Giorgio Valentini (IWBBIO, 2020)

Explainable Machine Learning for Early Assessment of COVID-19 Risk Prediction in Emergency Departments. - Elena Casiraghi; Dario Malchiodi; Gabriella Trucco; Marco Frasca 001; Luca Cappelletti; Tommaso Fontana; Alessandro Andrea Esposito; Emanuele Avola; Alessandro Jachetti; Justin T. Reese; Alessandro Rizzi; Peter N. Robinson; et al. (IEEE Access, 2020)

Complex Data Imputation by Auto-Encoders and Convolutional Neural Networks - A Case Study on Genome Gap-Filling. - Luca Cappelletti; Tommaso Fontana; Guido Walter Di Donato; Lorenzo Di Tucci; Elena Casiraghi; Giorgio Valentini (Comput., 2020)

Protein function prediction as a graph-transduction game. - Sebastiano Vascon; Marco Frasca 001; Rocco Tripodi; Giorgio Valentini; Marcello Pelillo (Pattern Recognit. Lett., 2020)

A Web Tool for the Semantic Integration of Heterogeneous and Complex Spreadsheet Tables. - Sara Bonfitto; Luca Cappelletti; Elena Casiraghi; Paolo Perlasca; Fabrizio Trovato; Giorgio Valentini; Marco Mesiti (SEBD, 2021)

Semi-automatic Column Type Inference for CSV Table Understanding. - Sara Bonfitto; Luca Cappelletti; Fabrizio Trovato; Giorgio Valentini; Marco Mesiti (SOFSEM, 2021)

HEMDAG: a family of modular and scalable hierarchical ensemble methods to improve Gene Ontology term prediction. - Marco Notaro; Marco Frasca 001; Alessandro Petrini; Jessica Gliozzo; Elena Casiraghi; Peter N. Robinson; Giorgio Valentini (Bioinform., 2021)

Het-node2vec: second order random walk sampling for heterogeneous multigraphs embedding. - Giorgio Valentini; Elena Casiraghi; Luca Cappelletti; Vida Ravanmehr; Tommaso Fontana; Justin T. Reese; Peter N. Robinson (CoRR, 2021)

GraPE: fast and scalable Graph Processing and Embedding. - Luca Cappelletti; Tommaso Fontana; Elena Casiraghi; Vida Ravanmehr; Tiffany J. Callahan; Marcin P. Joachimiak; Christopher J. Mungall; Peter N. Robinson; Justin T. Reese; Giorgio Valentini (CoRR, 2021)

Abdominal Computed Tomography Imaging Findings in Hospitalized COVID-19 Patients: A Year-Long Experience and Associations Revealed by Explainable Artificial Intelligence. - Alice Scarabelli; Massimo Zilocchi; Elena Casiraghi; Pierangelo Fasani; Guido Giovanni Plensich; Alessandro Andrea Esposito; Elvira Stellato; Alessandro Petrini; Justin T. Reese; Peter N. Robinson; Giorgio Valentini; Gianpaolo Carrafiello (J. Imaging, 2021)

Integration and Visual Analysis of Biomolecular Networks Through UNIPred-Web. - Paolo Perlasca; Marco Frasca 001; Cheick Tidiane Ba; Jessica Gliozzo; Marco Notaro; Mario Pennacchioni; Giorgio Valentini; Marco Mesiti (ICWE Workshops, 2022)

ParSMURF-NG: A Machine Learning High Performance Computing System for the Analysis of Imbalanced Big Omics Data. - Alessandro Petrini; Marco Notaro; Jessica Gliozzo; Tiziana Castrignanò; Peter N. Robinson; Elena Casiraghi; Giorgio Valentini (AIAI (Workshops), 2022)

Heterogeneous data integration methods for patient similarity networks. - Jessica Gliozzo; Marco Mesiti; Marco Notaro; Alessandro Petrini; Alex Patak; Antonio Puertas Gallardo; Alberto Paccanaro; Giorgio Valentini; Elena Casiraghi (Briefings Bioinform., 2022)

Boosting tissue-specific prediction of active cis-regulatory regions through deep learning and Bayesian optimization techniques. - Luca Cappelletti; Alessandro Petrini; Jessica Gliozzo; Elena Casiraghi; Max Schubach; Martin Kircher; Giorgio Valentini (BMC Bioinform., 2022)

Tell Bennet, Christopher Chute, Peter DeWitt, Kenneth Gersing, Andrew Girvin, Melissa Haendel, Jeremy Harper, Janos Hajagos, Stephanie Hong, Emily Pfaff, Jane Reusch, Corneliu Antoniescu, Kimberly Robaski: A Methodological Framework for the Comparative Evaluation of Multiple Imputation Methods: Multiple Imputation of Race, Ethnicity and Body Mass Index in the U.S. National COVID Cohort Collaborative. - Elena Casiraghi; Rachel Wong; Margaret Hall; Ben D. Coleman; Marco Notaro; Michael D. Evans; Jena S. Tronieri; Hannah Blau; Bryan Laraway; Tiffany J. Callahan; Lauren E. Chan; Carolyn T. Bramante; et al. (CoRR, 2022)

Patient Similarity Networks Integration for Partial Multimodal Datasets. - Jessica Gliozzo; Alex Patak; Antonio Puertas Gallardo; Elena Casiraghi; Giorgio Valentini (BIOINFORMATICS, 2023)

Intrinsic-Dimension Analysis for Guiding Dimensionality Reduction in Multi-Omics Data. - Valentina Guarino; Jessica Gliozzo; Ferdinando Clarelli; Béatrice Pignolet; Kaalindi Misra; Elisabetta Mascia; Giordano Antonino; Silvia Santoro; Laura Ferré; Miryam Cannizzaro; Melissa Sorosina; Roland Liblau; et al. (BIOINFORMATICS, 2023)

Degree-Normalization Improves Random-Walk-Based Embedding Accuracy in PPI Graphs. - Luca Cappelletti; Stefano Taverni; Tommaso Fontana; Marcin P. Joachimiak; Justin T. Reese; Peter N. Robinson; Elena Casiraghi; Giorgio Valentini (IWBBIO (2), 2023)

A Meta-Graph for the Construction of an RNA-Centered Knowledge Graph. - Emanuele Cavalleri; Sara Bonfitto; Alberto Cabri; Jessica Gliozzo; Paolo Perlasca; Mauricio Soto Gomez; Gabriella Trucco; Elena Casiraghi; Giorgio Valentini; Marco Mesiti (IWBBIO (1), 2023)

Towards the Construction of an RNA-centered Knowledge Graph. - Emanuele Cavalleri; Sara Bonfitto; Alberto Cabri; Jessica Gliozzo; Paolo Perlasca; Mauricio Soto Gomez; Gabriella Trucco; Elena Casiraghi; Giorgio Valentini; Marco Mesiti (SEBD, 2023)

An Open-Source Knowledge Graph Ecosystem for the Life Sciences. - Tiffany J. Callahan; Ignacio J. Tripodi; Adrianne L. Stefanski; Luca Cappelletti; Sanya Bathla Taneja; Jordan M. Wyrwa; Elena Casiraghi; Nicolas A. Matentzoglu; Justin T. Reese; Jonathan C. Silverstein; Charles Tapley Hoyt; Richard D. Boyce; et al. (CoRR, 2023)

RNA-KG: An ontology-based knowledge graph for representing interactions involving RNA molecules. - Emanuele Cavalleri; Alberto Cabri; Mauricio Soto Gomez; Sara Bonfitto; Paolo Perlasca; Jessica Gliozzo; Tiffany J. Callahan; Justin T. Reese; Peter N. Robinson; Elena Casiraghi; Giorgio Valentini; Marco Mesiti (CoRR, 2023)

GRAPE for fast and scalable graph processing and random-walk-based embedding. - Luca Cappelletti; Tommaso Fontana; Elena Casiraghi; Vida Ravanmehr; Tiffany J. Callahan; Carlos Cano; Marcin P. Joachimiak; Christopher J. Mungall; Peter N. Robinson; Justin T. Reese; Giorgio Valentini (Nat. Comput. Sci., 2023)

A method for comparing multiple imputation techniques: A case study on the U.S. national COVID cohort collaborative. - Elena Casiraghi; Rachel Wong; Margaret Hall; Ben D. Coleman; Marco Notaro; Michael D. Evans; Jena S. Tronieri; Hannah Blau; Bryan Laraway; Tiffany J. Callahan; Lauren E. Chan; Carolyn T. Bramante; et al. (J. Biomed. Informatics, 2023)

An expectation-maximization framework for comprehensive prediction of isoform-specific functions. - Guy Karlebach; Leigh Carmody; Jagadish Chandrabose Sundaramurthi; Elena Casiraghi; Peter Hansen; Justin T. Reese; Christopher J. Mungall; Giorgio Valentini; Peter N. Robinson (Bioinform., 2023)

The promises of large language models for protein design and modeling. - Giorgio Valentini; Dario Malchiodi; Jessica Gliozzo; Marco Mesiti; Mauricio Soto Gomez; Alberto Cabri; Justin T. Reese; Elena Casiraghi; Peter N. Robinson (Frontiers Bioinform., 2023)

Fine-Tuning of Conditional Transformers Improves the Generation of Functionally Characterized Proteins. - Marco Nicolini; Dario Malchiodi; Alberto Cabri; Emanuele Cavalleri; Marco Mesiti; Alberto Paccanaro; Peter N. Robinson; Justin T. Reese; Elena Casiraghi; Giorgio Valentini (BIOSTEC (1), 2024)

Initial achievements in relation extraction from RNA-focused scientific papers. - Emanuele Cavalleri; Mauricio Soto Gomez; Ali Pashaeibarough; Dario Malchiodi; J. Harry Caufield; Justin T. Reese; Christopher J. Mungall; Peter N. Robinson; Elena Casiraghi; Giorgio Valentini; Marco Mesiti (SEBD, 2024)

SPIREX: Improving LLM-based relation extraction from RNA-focused scientific literature using graph machine learning. - Emanuele Cavalleri; Mauricio Soto Gomez; Ali Pashaeibarough; Dario Malchiodi; J. Harry Caufield; Justin T. Reese; Chris Mungall; Peter N. Robinson; Elena Casiraghi; Giorgio Valentini; Marco Mesiti (VLDB Workshops, 2024)

Predicting nutrition and environmental factors associated with female reproductive disorders using a knowledge graph and random forests. - Lauren E. Chan; Elena Casiraghi; Justin T. Reese; Quaker E. Harmon; Kevin Schaper; Harshad Hegde; Giorgio Valentini; Charles Schmitt; Alison A. Motsinger-Reif; Janet E. Hall; Christopher J. Mungall; Peter N. Robinson; et al. (Int. J. Medical Informatics, 2024)

Intrinsic-dimension analysis for guiding dimensionality reduction and data fusion in multi-omics data processing. - Jessica Gliozzo; Mauricio Soto Gomez; Valentina Guarino; Arturo Bonometti; Alberto Cabri; Emanuele Cavalleri; Justin T. Reese; Peter N. Robinson; Marco Mesiti; Giorgio Valentini; Elena Casiraghi (Artif. Intell. Medicine, 2025)