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Luca Alessandri

Showing results (1-10 of 17) with videos related to

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Methods in Molecular Biology (Clifton, N.J.)|December 10, 2022
Identifying Gene Markers Associated with Cell SubpopulationsMaria Luisa Ratto, Luca Alessandri
Methods in Molecular Biology (Clifton, N.J.)|December 10, 2022
Functional-Feature-Based Data Reduction Using Sparsely Connected AutoencodersLuca Alessandri, Raffaele A Calogero
Methods in Molecular Biology (Clifton, N.J.)|December 10, 2022
Bringing Cell Subpopulation Discovery on a Cloud-HPC Using rCASC and StreamFlowSandro G Contaldo, Luca Alessandri, Iacopo Colonnelli, et al.
Methods in Molecular Biology (Clifton, N.J.)|December 10, 2022
Using "Galaxy-rCASC": A Public Galaxy Instance for Single-Cell RNA-Seq Data AnalysisPietro Mandreoli, Luca Alessandri, Raffaele A Calogero, et al.
Bioinformatics Advances|March 13, 2026
GPTBioInsightor-leveraging large language models for transparent scRAN-seq cell type annotationsShenghui Huang, Berina Šabanović, Yuzhong Peng, et al.
Blood|August 18, 2025
Epigenetic changes by EZH2 inhibition increase translocations in B cells with high AID activity or DNA repair deficiencyJianli Tao, Luca Alessandri, Alessandro Gasparetto, et al.
International Journal of Molecular Sciences|December 10, 2021
Sparsely Connected Autoencoders: A Multi-Purpose Tool for Single Cell omics AnalysisLuca Alessandri, Maria Luisa Ratto, Sandro Gepiro Contaldo, et al.
Scientific Data|February 2, 2024
A single cell RNAseq benchmark experiment embedding "controlled" cancer heterogeneityMaddalena Arigoni, Maria Luisa Ratto, Federica Riccardo, et al.
NPJ Systems Biology and Applications|January 6, 2021
Sparsely-connected autoencoder (SCA) for single cell RNAseq data miningLuca Alessandri, Francesca Cordero, Marco Beccuti, et al.
BMC Bioinformatics|March 13, 2024
CREDO: a friendly Customizable, REproducible, DOcker file generator for bioinformatics applicationsSimone Alessandri, Maria L Ratto, Sergio Rabellino, et al.
Pageof 2

Showing results (1-10 of 17) with videos related to

Sort By:
Pageof 2
Methods in Molecular Biology (Clifton, N.J.)|December 10, 2022
Identifying Gene Markers Associated with Cell SubpopulationsMaria Luisa Ratto, Luca Alessandri
Methods in Molecular Biology (Clifton, N.J.)|December 10, 2022
Functional-Feature-Based Data Reduction Using Sparsely Connected AutoencodersLuca Alessandri, Raffaele A Calogero
Methods in Molecular Biology (Clifton, N.J.)|December 10, 2022
Bringing Cell Subpopulation Discovery on a Cloud-HPC Using rCASC and StreamFlowSandro G Contaldo, Luca Alessandri, Iacopo Colonnelli, et al.
Methods in Molecular Biology (Clifton, N.J.)|December 10, 2022
Using "Galaxy-rCASC": A Public Galaxy Instance for Single-Cell RNA-Seq Data AnalysisPietro Mandreoli, Luca Alessandri, Raffaele A Calogero, et al.
Bioinformatics Advances|March 13, 2026
GPTBioInsightor-leveraging large language models for transparent scRAN-seq cell type annotationsShenghui Huang, Berina Šabanović, Yuzhong Peng, et al.
Blood|August 18, 2025
Epigenetic changes by EZH2 inhibition increase translocations in B cells with high AID activity or DNA repair deficiencyJianli Tao, Luca Alessandri, Alessandro Gasparetto, et al.
International Journal of Molecular Sciences|December 10, 2021
Sparsely Connected Autoencoders: A Multi-Purpose Tool for Single Cell omics AnalysisLuca Alessandri, Maria Luisa Ratto, Sandro Gepiro Contaldo, et al.
Scientific Data|February 2, 2024
A single cell RNAseq benchmark experiment embedding "controlled" cancer heterogeneityMaddalena Arigoni, Maria Luisa Ratto, Federica Riccardo, et al.
NPJ Systems Biology and Applications|January 6, 2021
Sparsely-connected autoencoder (SCA) for single cell RNAseq data miningLuca Alessandri, Francesca Cordero, Marco Beccuti, et al.
BMC Bioinformatics|March 13, 2024
CREDO: a friendly Customizable, REproducible, DOcker file generator for bioinformatics applicationsSimone Alessandri, Maria L Ratto, Sergio Rabellino, et al.
Pageof 2