Drug Repositioning Predictions by Non-Negative Matrix Tri-Factorization of Integrated Association Data. - Gaëtan Dissez; Gaia Ceddia; Pietro Pinoli; Stefano Ceri; Marco Masseroli (BCB, 2019)

Using GMQL-Web for Querying, Downloading and Integrating Public with Private Genomic Datasets. - Marzia Settino; Anna Bernasconi 002; Gaia Ceddia; Giuseppe Agapito; Marco Masseroli; Mario Cannataro (BCB, 2019)

Network Modeling and Analysis of Normal and Cancer Gene Expression Data. - Gaia Ceddia; Sara Pidò; Marco Masseroli (CIBB, 2019)

Non-negative Matrix Tri-Factorization for Data Integration and Network-based Drug Repositioning. - Gaia Ceddia; Pietro Pinoli; Stefano Ceri; Marco Masseroli (CIBCB, 2019)

Association rule mining to identify transcription factor interactions in genomic regions. - Gaia Ceddia; Liuba Nausicaa Martino; Alice C. L. Parodi; Piercesare Secchi; Stefano Campaner; Marco Masseroli (Bioinform., 2020)

Matrix Factorization-based Technique for Drug Repurposing Predictions. - Gaia Ceddia; Pietro Pinoli; Stefano Ceri; Marco Masseroli (IEEE J. Biomed. Health Informatics, 2020)

Computational methods for data-driven predictions and understanding of biological interactions. - Gaia Ceddia (2021)

Predicting Drug Synergism by Means of Non-Negative Matrix Tri-Factorization. - Pietro Pinoli; Gaia Ceddia; Stefano Ceri; Marco Masseroli (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

Inferring Breast Cancer Subtype Associations Using an Original Omics Integration Based on Non-negative Matrix Tri-Factorization. - Camila Riccio-Rengifo; Silvia Cascianelli; Gaia Ceddia; Marco Masseroli (CIBB, 2023)

A functional analysis of omic network embedding spaces reveals key altered functions in cancer. - Sergio Doria-Belenguer; Alexandros Xenos; Gaia Ceddia; Noël Malod-Dognin; Natasa Przulj (Bioinform., 2023)

Identification of transcription factor high accumulation DNA zones. - Silvia Cascianelli; Gaia Ceddia; Alberto Marchesi; Marco Masseroli (BMC Bioinform., 2023)