ANTONIOTTI MARCO

Ruolo:

Professore associato

Settore scientifico disciplinare:

INFORMATICA (INF/01)

Afferenza:

E-mail:

Telefono:

0264487901

Stanza:

U14, Piano: P02, Stanza: 2043
Viale Sarca, 336 - 20126 MILANO

Omrani, M., Calabria, A., Antoniotti, M., & Aiuti, A. (In corso di stampa). Application of Random Forest algorithm for Prediction of False positive Insertion sites in gene therapy treated patient’s integrome profile. Intervento presentato a: RECOMB - Computational Cancer Biology 2020, Padua, Italy. Dettaglio
Ramazzotti., D., Angaroni, F., Maspero, D., Gambacorti-Passerini, C., Antoniotti, M., Graudenzi, A., et al. (2021). VERSO: a comprehensive framework for the inference of robust phylogenies and the quantification of intra-host genomic diversity of viral samples. PATTERNS, 2(3). Dettaglio
Ramazzotti, D., Angaroni, F., Maspero, D., Ascolani, G., Castiglioni, I., Piazza, R., et al. (2021). Variant calling from scRNA-seq data allows the assessment of cellular identity in patient-derived cell lines [Altro]. Dettaglio
Craigher, F., Angaroni, F., Graudenzi, A., Stella, F., & Antoniotti, M. (2020). Investigating the Compositional Structure Of Deep Neural Networks. In The Sixth International Conference on Machine Learning, Optimization, and Data Science. Dettaglio
Ramazzotti, D., Angaroni, F., Maspero, D., Gambacorti-Passerini, C., Antoniotti, M., Graudenzi, A., et al. (2020). Characterization of intra-host SARS-CoV-2 variants improves phylogenomic reconstruction and may reveal functionally convergent mutations [Rapporto tecnico]. Dettaglio

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