CASCIANELLI, SILVIA
CASCIANELLI, SILVIA
DIPARTIMENTO DI ELETTRONICA, INFORMAZIONE E BIOINGEGNERIA
A data science approach to investigate the mutational landscape of a critical patient subgroup
2024-01-01 Cascianelli, Silvia; Iudica, Cristina; Masseroli, Marco
Adapting feature selection in gene expression-based classification for higher biological interpretability
2023-01-01 Mongardi, S.; Cascianelli, S.; Masseroli, M.
Biologically weighted LASSO: enhancing functional interpretability in gene expression data analysis
2024-01-01 Mongardi, Sofia; Cascianelli, Silvia; Masseroli, Marco
Biologically-driven feature selection for improved functional interpretability of gene expression data analysis
2023-01-01 Mongardi, S.; Cascianelli, S.; Masseroli, M.
Boosting perspectives for breast cancer intrinsic subtyping on RNA-sequencing data
2020-01-01 Cascianelli, S; Molineris, I; Isella, C; Masseroli, M; Medico, E
Comparing classic, deep and semi-supervised learning for whole-transcriptome breast cancer subtyping
2019-01-01 Cristovao, F; Canakoglu, A; Carman, M; Cascianelli, S; Nanni, L; Pinoli, P; Masseroli, M
Enhancing feature selection with biological insights: a novel forward approach for gene selection
2024-01-01 Mongardi, Sofia; Cascianelli, Silvia; Masseroli, Marco
Evaluating Deep Semi-supervised Learning for Whole-Transcriptome Breast Cancer Subtyping
2020-01-01 Cascianelli, Silvia; Cristovao, Francisco; Canakoglu, Arif; Carman, Mark; Nanni, Luca; Pinoli, Pietro; Masseroli, Marco
Gene co-expression network analysis for identifying cell populations in RNA-seq patient-derived xenografts
2023-01-01 Tome', Simone; Cascianelli, Silvia; Medico, Enzo; Isella, Claudio; Masseroli, Marco.
Gene expression-based multi-label classification to face colorectal cancer heterogeneity and provide biologically and clinically relevant traits
2022-01-01 Barbera, C; Cascianelli, S; Ulla, Aa; Grassi, E; Lupo, B; Pasini, D; Bertotti, A; Trusolino, L; Medico, E; Isella, C; Masseroli, M
Hybrid evolutionary framework for selection of genes predicting breast cancer relapse
2020-01-01 Perino, L; Cascianelli, S; Masseroli, M
Identification of transcription factor high accumulation DNA zones
2023-01-01 Cascianelli, S.; Ceddia, G.; Marchesi, A.; Masseroli, M.
Investigating Deep Learning based Breast Cancer Subtyping using Pan-cancer and Multi-omic Data
2022-01-01 Cristovao, F.; Cascianelli, S.; Canakoglu, A.; Carman, M.; Nanni, L.; Pinoli, P.; Masseroli, M.
Investigating transcript isoform RNA-seq data and machine learning techniques for breast cancer subtyping
2021-01-01 Cascianelli, S; Sanatdoost, Sn; Masseroli, M.
Machine learning for multi-label subtyping: a key to dissecting intra-tumor heterogeneity at the bulk sample level
2023-01-01 Cascianelli, Silvia; Masseroli, Marco
Machine learning for RNA sequencing-based intrinsic subtyping of breast cancer
2020-01-01 Cascianelli, S.; Molineris, I.; Isella, C.; Masseroli, M.; Medico, E.
Machine learning to discover genes predictive of RAS-mutated cases in mutational profiles of colorectal cancer patients.
2022-01-01 Bellomo, M; Cascianelli, S; Medico, E; Masseroli, M.
Multi-label transcriptional classification of colorectal cancer reflects tumor cell population heterogeneity
2023-01-01 Cascianelli, Silvia; Barbera, Chiara; Ambra Ulla, Alexandra; Grassi, Elena; Lupo, Barbara; Pasini, Diego; Bertotti, Andrea; Trusolino, Livio; Medico, Enzo; Isella &, Claudio; Masseroli, Marco
Multi-label transcriptional classification of colorectal cancer reflects tumour cell population heterogeneity
2023-01-01 Cascianelli, S; Barbera, C; Ulla, Aa; Grassi, E; Lupo, B; Pasini, D; Bertotti, A; Trusolino, L; Medico, E; Isella, C; Masseroli, M
Multi-label transcriptional classification of colorectal cancer reflects tumour cell population heterogeneity
2023-01-01 Cascianelli, S; Barbera, C; Ulla, Aa; Grassi, E; Lupo, B; Pasini, D; Bertotti, A; Trusolino, L; Medico, E; Isella, C; Masseroli, M.