Learning to classify species with barcodes. - Paola Bertolazzi; Giovanni Felici; Emanuel Weitschek (BMC Bioinform., 2009)

MALA: A Microarray Clustering and Classification Software. - Emanuel Weitschek; Giovanni Felici; Paola Bertolazzi (DEXA Workshops, 2012)

Mining logic models in the presence of noisy data. - Giovanni Felici; Emanuel Weitschek (ISAIM, 2012)

Clinical Data Mining: Problems, Pitfalls and Solutions. - Emanuel Weitschek; Giovanni Felici; Paola Bertolazzi (DEXA Workshops, 2013)

Alzheimer's disease patients classification through EEG signals processing. - Giulia Fiscon; Emanuel Weitschek; Giovanni Felici; Paola Bertolazzi; Simona De Salvo; Placido Bramanti; Maria Cristina De Cola (CIDM, 2014)

Classifying Bacterial Genomes with Compact Logic Formulas on k-Mer Frequencies. - Emanuel Weitschek; Fabio Cunial; Giovanni Felici (DEXA Workshops, 2014)

Supervised DNA Barcodes species classification: analysis, comparisons and results. - Emanuel Weitschek; Giulia Fiscon; Giovanni Felici (BioData Min., 2014)

GELA: A Software Tool for the Analysis of Gene Expression Data. - Emanuel Weitschek; Giulia Fiscon; Giovanni Felici; Paola Bertolazzi (DEXA Workshops, 2015)

LAF: Logic Alignment Free and its application to bacterial genomes classification. - Emanuel Weitschek; Fabio Cunial; Giovanni Felici (BioData Min., 2015)

IRIS-TCGA: An Information Retrieval and Integration System for Genomic Data of Cancer. - Fabio Cumbo; Emanuel Weitschek; Paola Bertolazzi; Giovanni Felici (CIBB, 2016)

Genomic Data Integration: A Case Study on Next Generation Sequencing of Cancer. - Emanuel Weitschek; Fabio Cumbo; Eleonora Cappelli; Giovanni Felici (DEXA Workshops, 2016)

MISSEL: a method to identify a large number of small species-specific genomic subsequences and its application to viruses classification. - Giulia Fiscon; Emanuel Weitschek; Eleonora Cella; Alessandra Lo Presti; Marta Giovanetti; Muhammed Babakir-Mina; Marco Ciotti; Massimo Ciccozzi; Alessandra Pierangeli; Paola Bertolazzi; Giovanni Felici (BioData Min., 2016)

CAMUR: Knowledge extraction from RNA-seq cancer data through equivalent classification rules. - Valerio Cestarelli; Giulia Fiscon; Giovanni Felici; Paola Bertolazzi; Emanuel Weitschek (Bioinform., 2016)

Integer programming models for feature selection: New extensions and a randomized solution algorithm. - Paola Bertolazzi; Giovanni Felici; Paola Festa; Giulia Fiscon; Emanuel Weitschek (Eur. J. Oper. Res., 2016)

Optimal discretization and selection of features by association rates of joint distributions. - Daniele Santoni; Emanuel Weitschek; Giovanni Felici (RAIRO Oper. Res., 2016)

Highlights from the 11th ISCB Student Council Symposium 2015: Dublin, Ireland. 10 July 2015. - Katie Wilkins; Mehedi Hassan; Margherita Francescatto; Jakob B. Jespersen; R. Gonzalo Parra; Bart Cuypers; Dan F. DeBlasio; Alexander Junge; Anupama Jigisha; Farzana Rahman; Griet Laenen; Sander Willems; et al. (BMC Bioinform., 2016)

String-Matching and Alignment Algorithms for Finding Motifs in NGS Data. - Giulia Fiscon; Emanuel Weitschek (Algorithms for Next-Generation Sequencing Data, 2017)

Smart open online tool for adaptive education on Cloud Computing. - Dario Assante; Claudio Fornaro; Emanuel Weitschek; Manuel Castro 001; Sergio Martín 001; Ileana Hamburg; Aisling Owens; Ricardo Tavio Gallo; Kostas Konstantinou; Stekoulis Spyros; Alcino Pascoal; Catarina Reis; et al. (EDUCON, 2017)

Extending the Genomic Data Model and the Genometric Query Language with Domain Taxonomies. - Eleonora Cappelli; Emanuel Weitschek (ICWE, 2017)

TCGA2BED: extracting, extending, integrating, and querying The Cancer Genome Atlas. - Fabio Cumbo; Giulia Fiscon; Stefano Ceri; Marco Masseroli; Emanuel Weitschek (BMC Bioinform., 2017)

A novel method and software for automatically classifying Alzheimer's disease patients by magnetic resonance imaging analysis. - Fabio Previtali; Paola Bertolazzi; Giovanni Felici; Emanuel Weitschek (Comput. Methods Programs Biomed., 2017)

An integrated approach based on EEG signals processing combined with supervised methods to classify Alzheimer's disease patients. - Giulia Fiscon; Emanuel Weitschek; Maria Cristina De Cola; Giovanni Felici; Paola Bertolazzi (BIBM, 2018)

Classifying Big DNA Methylation Data: A Gene-Oriented Approach. - Emanuel Weitschek; Fabio Cumbo; Eleonora Cappelli; Giovanni Felici; Paola Bertolazzi (DEXA Workshops, 2018)

Classification of Large DNA Methylation Datasets for Identifying Cancer Drivers. - Fabrizio Celli; Fabio Cumbo; Emanuel Weitschek (Big Data Res., 2018)

Combining DNA methylation and RNA sequencing data of cancer for supervised knowledge extraction. - Eleonora Cappelli; Giovanni Felici; Emanuel Weitschek (BioData Min., 2018)

CamurWeb: a classification software and a large knowledge base for gene expression data of cancer. - Emanuel Weitschek; Silvia Di Lauro; Eleonora Cappelli; Paola Bertolazzi; Giovanni Felici (BMC Bioinform., 2018)

Combining EEG signal processing with supervised methods for Alzheimer's patients classification. - Giulia Fiscon; Emanuel Weitschek; Alessio Cialini; Giovanni Felici; Paola Bertolazzi; Simona De Salvo; Alessia Bramanti; Placido Bramanti; Maria Cristina De Cola (BMC Medical Informatics Decis. Mak., 2018)

Extending Knowledge on Genomic Data and Metadata of Cancer by Exploiting Taxonomy-Based Relaxed Queries on Domain-Specific Ontologies. - Eleonora Cappelli; Emanuel Weitschek; Fabio Cumbo (CIBB, 2019)

Smart Persistence and Accessibility of Genomic and Clinical Data. - Eleonora Cappelli; Emanuel Weitschek; Fabio Cumbo (DEXA Workshops, 2019)

Novel algorithm to extract multiple solutions for RNA sequence classification problem. - Naoual Guannoni; Faouzi Mhamdi; Emanuel Weitschek; Mourad Elloumi (HPCS, 2019)

An In-Memory Cognitive-Based Hyperdimensional Approach to Accurately Classify DNA-Methylation Data of Cancer. - Fabio Cumbo; Emanuel Weitschek (DEXA Workshops, 2020)

A Brain-Inspired Hyperdimensional Computing Approach for Classifying Massive DNA Methylation Data of Cancer. - Fabio Cumbo; Eleonora Cappelli; Emanuel Weitschek (Algorithms, 2020)

SP-BRAIN: scalable and reliable implementations of a supervised relevance-based machine learning algorithm. - Valerio Morfino; Salvatore Rampone; Emanuel Weitschek (Soft Comput., 2020)

A Comparison of Apache Spark Supervised Machine Learning Algorithms for DNA Splicing Site Prediction. - Valerio Morfino; Salvatore Rampone; Emanuel Weitschek (Neural Approaches to Dynamics of Signal Exchanges, 2020)

OpenGDC. - Fabio Cumbo; Eleonora Cappelli; Anna Bernasconi 002; Arif Canakoglu; Stefano Ceri; Marco Masseroli; Emanuel Weitschek (Zenodo, 2020)

Price Discrimination in the Online Airline Market: An Empirical Study. - Stefano Azzolina; Manuel Razza; Kevin Sartiano; Emanuel Weitschek (J. Theor. Appl. Electron. Commer. Res., 2021)

hdlib: A Python library for designing Vector-Symbolic Architectures. - Fabio Cumbo; Emanuel Weitschek; Daniel Blankenberg (J. Open Source Softw., 2023)

Feature selection with vector-symbolic architectures: a case study on microbial profiles of shotgun metagenomic samples of colorectal cancer. - Fabio Cumbo; Simone Truglia; Emanuel Weitschek; Daniel Blankenberg (Briefings Bioinform., 2024)