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Silvia Cascianelli

Showing results (1-10 of 15) with videos related to

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Methods in Molecular Biology (Clifton, N.J.)|December 13, 2021
Scenarios for the Integration of Microarray Gene Expression Profiles in COVID-19-Related StudiesAnna Bernasconi, Silvia Cascianelli
BMC Bioinformatics|April 8, 2022
RGMQL: scalable and interoperable computing of heterogeneous omics big data and metadata in R/BioconductorSimone Pallotta, Silvia Cascianelli, Marco Masseroli
Journal of Biomedical Informatics|July 24, 2023
Supervised Relevance-Redundancy assessments for feature selection in omics-based classification scenariosSilvia Cascianelli, Arianna Galzerano, Marco Masseroli
Bioinformatics (Oxford, England)|October 16, 2024
Biologically weighted LASSO: enhancing functional interpretability in gene expression data analysisSofia Mongardi, Silvia Cascianelli, Marco Masseroli
Journal of Biomedical Informatics|April 11, 2025
A novel machine learning-based workflow to capture intra-patient heterogeneity through transcriptional multi-label characterization and clinically relevant classificationSilvia Cascianelli, Iva Milojkovic, Marco Masseroli
BMC Bioinformatics|October 20, 2023
Identification of transcription factor high accumulation DNA zonesSilvia Cascianelli, Gaia Ceddia, Alberto Marchesi, et al.
Scientific Reports|August 23, 2020
Machine learning for RNA sequencing-based intrinsic subtyping of breast cancerSilvia Cascianelli, Ivan Molineris, Claudio Isella, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|February 7, 2022
From Show to Tell: A Survey on Deep Learning-Based Image CaptioningMatteo Stefanini, Marcella Cornia, Lorenzo Baraldi, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|October 15, 2024
VATr++: Choose Your Words Wisely for Handwritten Text GenerationBram Vanherle, Vittorio Pippi, Silvia Cascianelli, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics|December 3, 2020
Investigating Deep Learning Based Breast Cancer Subtyping Using Pan-Cancer and Multi-Omic DataFrancisco Cristovao, Silvia Cascianelli, Arif Canakoglu, et al.
Pageof 2

Showing results (1-10 of 15) with videos related to

Sort By:
Pageof 2
Methods in Molecular Biology (Clifton, N.J.)|December 13, 2021
Scenarios for the Integration of Microarray Gene Expression Profiles in COVID-19-Related StudiesAnna Bernasconi, Silvia Cascianelli
BMC Bioinformatics|April 8, 2022
RGMQL: scalable and interoperable computing of heterogeneous omics big data and metadata in R/BioconductorSimone Pallotta, Silvia Cascianelli, Marco Masseroli
Journal of Biomedical Informatics|July 24, 2023
Supervised Relevance-Redundancy assessments for feature selection in omics-based classification scenariosSilvia Cascianelli, Arianna Galzerano, Marco Masseroli
Bioinformatics (Oxford, England)|October 16, 2024
Biologically weighted LASSO: enhancing functional interpretability in gene expression data analysisSofia Mongardi, Silvia Cascianelli, Marco Masseroli
Journal of Biomedical Informatics|April 11, 2025
A novel machine learning-based workflow to capture intra-patient heterogeneity through transcriptional multi-label characterization and clinically relevant classificationSilvia Cascianelli, Iva Milojkovic, Marco Masseroli
BMC Bioinformatics|October 20, 2023
Identification of transcription factor high accumulation DNA zonesSilvia Cascianelli, Gaia Ceddia, Alberto Marchesi, et al.
Scientific Reports|August 23, 2020
Machine learning for RNA sequencing-based intrinsic subtyping of breast cancerSilvia Cascianelli, Ivan Molineris, Claudio Isella, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|February 7, 2022
From Show to Tell: A Survey on Deep Learning-Based Image CaptioningMatteo Stefanini, Marcella Cornia, Lorenzo Baraldi, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|October 15, 2024
VATr++: Choose Your Words Wisely for Handwritten Text GenerationBram Vanherle, Vittorio Pippi, Silvia Cascianelli, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics|December 3, 2020
Investigating Deep Learning Based Breast Cancer Subtyping Using Pan-Cancer and Multi-Omic DataFrancisco Cristovao, Silvia Cascianelli, Arif Canakoglu, et al.
Pageof 2