CASCIANELLI, SILVIA

CASCIANELLI, SILVIA  

DIPARTIMENTO DI ELETTRONICA, INFORMAZIONE E BIOINGEGNERIA  

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Titolo Data di pubblicazione Autori File
Adapting feature selection in gene expression-based classification for higher biological interpretability 1-gen-2023 S. MongardiS. CascianelliM. Masseroli
Biologically-driven feature selection for improved functional interpretability of gene expression data analysis 1-gen-2023 S. MongardiS. CascianelliM. Masseroli
Boosting perspectives for breast cancer intrinsic subtyping on RNA-sequencing data 1-gen-2020 S CascianelliM Masseroli +
Comparing classic, deep and semi-supervised learning for whole-transcriptome breast cancer subtyping 1-gen-2019 A CanakogluM CarmanS CascianelliL NanniP PinoliM Masseroli +
Evaluating Deep Semi-supervised Learning for Whole-Transcriptome Breast Cancer Subtyping 1-gen-2020 Cascianelli, SilviaCristovao, FranciscoCanakoglu, ArifCarman, MarkNanni, LucaPinoli, PietroMasseroli, Marco
Gene co-expression network analysis for identifying cell populations in RNA-seq patient-derived xenografts 1-gen-2023 Tome SimoneCascianelli SilviaMasseroli Marco. +
Gene expression-based multi-label classification to face colorectal cancer heterogeneity and provide biologically and clinically relevant traits 1-gen-2022 Cascianelli SMasseroli M +
Hybrid evolutionary framework for selection of genes predicting breast cancer relapse 1-gen-2020 L PerinoS CascianelliM Masseroli
Identification of transcription factor high accumulation DNA zones 1-gen-2023 Cascianelli S.Ceddia G.Masseroli M. +
Investigating Deep Learning based Breast Cancer Subtyping using Pan-cancer and Multi-omic Data 1-gen-2022 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 1-gen-2021 Cascianelli SMasseroli M. +
Machine learning for multi-label subtyping: a key to dissecting intra-tumor heterogeneity at the bulk sample level 1-gen-2023 Silvia CascianelliMarco Masseroli
Machine learning for RNA sequencing-based intrinsic subtyping of breast cancer 1-gen-2020 Cascianelli S.Masseroli M. +
Machine learning to discover genes predictive of RAS-mutated cases in mutational profiles of colorectal cancer patients. 1-gen-2022 Cascianelli SMasseroli M. +
Multi-label transcriptional classification of colorectal cancer reflects tumor cell population heterogeneity 1-gen-2023 Silvia CascianelliChiara BarberaMarco Masseroli +
Multi-label transcriptional classification of colorectal cancer reflects tumour cell population heterogeneity 1-gen-2023 Cascianelli SBarbera CMasseroli M +
Multi-label transcriptional classification of colorectal cancer reflects tumour cell population heterogeneity 1-gen-2023 Cascianelli SBarbera CMasseroli M. +
Non-negative Matrix Tri-Factorization for data integration and knowledge inference on breast cancer subtyping 1-gen-2023 Silvia CascianelliGaia CeddiaMarco Masseroli. +
RGMQL: scalable and interoperable computing of heterogeneous omics big data and metadata in R/Bioconductor 1-gen-2022 Cascianelli, SilviaMasseroli, Marco +
Scenarios for the Integration of Microarray Gene Expression Profiles in COVID-19-Related Studies 1-gen-2022 Bernasconi, AnnaCascianelli, Silvia