Salvatore Milite

PITA 02.011

Human Technopole

20157, Milan, MI

I am a graduate student in computational biology in the Lab of Prof. Andrea Sottoriva at Human Technopole, co-supervised by Prof. Giulio Caravagna at the University of Trieste. I also have a Master’s degree in Data Science and Scientifi Computing from the University of Trieste and SISSA. My main interests are statistical learning and generative models. I have years of experience in developing tools for the analysis of NGS data. Currently, I am focusing on developing deep generative methods to analyze and integrate single-cell multi-omics data, with a particular focus on understanding cancer evolution under therapy. I am also extremely excited about hierarchical models (hierachical VAEs are my obsession rn) and the theory of hierarchy in complex systems (this gives a good idea of what I am talking about)

In reality, I am basically into every challenging problem that has some maths and stats in it (bonus point if there is biology), so if you are interested in what I do or you want to talk science (and maybe have a cool scientific problem to disucss) feel free to get in touch either by email or on social media.

news

May 25, 2024	I will be presenting my work at the EMBO conference The many faces of cancer evolution in Rimini, see you there.
May 01, 2024	I have been admitted to the Generative Modeling Summer School taking place in Eindhoven, June 24-28th. Very excited to learn more about my favourite topic with lots of great instructors.
Apr 09, 2024	Our preprint on Multiomics Archetypal Analysis is now finally available online.
Jan 31, 2024	Our preprint on exploiting Neural ODEs for computing RNA velocity in scRNA-seq in online.
Jan 31, 2024	Our new work Computational validation of clonal and subclonal copy number alterations from bulk tumor sequencing using CNAqc is out on Genome Biology.

selected publications

Deep Archetypal Analysis for interpretable multi-omic data integration based on biological principles

Salvatore Milite, Giulio Caravagna, and Andrea Sottoriva

bioRxiv, 2024

Bib

@article{milite2024deep,
  title = {Deep Archetypal Analysis for interpretable multi-omic data integration based on biological principles},
  author = {Milite, Salvatore and Caravagna, Giulio and Sottoriva, Andrea},
  journal = {bioRxiv},
  pages = {2024--04},
  year = {2024},
  publisher = {Cold Spring Harbor Laboratory},
}

Clinical application of tumour-in-normal contamination assessment from whole genome sequencing

Jonathan Mitchell, Salvatore Milite, Jack Bartram, and 8 more authors

Nature Communications, 2024

Bib

@article{mitchell2024clinical,
  title = {Clinical application of tumour-in-normal contamination assessment from whole genome sequencing},
  author = {Mitchell, Jonathan and Milite, Salvatore and Bartram, Jack and Walker, Susan and Volkova, Nadezda and Yavorska, Olena and Zarowiecki, Magdalena and Chalker, Jane and Thomas, Rebecca and Vago, Luca and others},
  journal = {Nature Communications},
  volume = {15},
  number = {1},
  pages = {323},
  year = {2024},
  publisher = {Nature Publishing Group UK London},
}

NeuroVelo: interpretable learning of cellular dynamics from single-cell transcriptomic data

Idris Kouadri Boudjelthia, Salvatore Milite, Nour El Kazwini, and 5 more authors

bioRxiv, 2023

Bib

@article{kouadri2023neurovelo,
  title = {NeuroVelo: interpretable learning of cellular dynamics from single-cell transcriptomic data},
  author = {Kouadri Boudjelthia, Idris and Milite, Salvatore and El Kazwini, Nour and Fernandez-Mateos, Javier and Valeri, Nicola and Huang, Yuanhua and Sottoriva, Andrea and Sanguinetti, Guido},
  journal = {bioRxiv},
  pages = {2023--11},
  year = {2023},
  publisher = {Cold Spring Harbor Laboratory},
}

Epigenetic heritability of cell plasticity drives cancer drug resistance through one-to-many genotype to phenotype mapping

Javier Fernandez-Mateos, Salvatore Milite, Erica Oliveira, and 8 more authors

bioRxiv, 2023

Bib

@article{fernandez2023epigenetic,
  title = {Epigenetic heritability of cell plasticity drives cancer drug resistance through one-to-many genotype to phenotype mapping},
  author = {Fernandez-Mateos, Javier and Milite, Salvatore and Oliveira, Erica and Vlachogiannis, Georgios and Chen, Bingjie and Yara, Erika and Cresswell, George D and James, Chela and Patruno, Lucrezia and Ascolani, Gianluca and others},
  journal = {bioRxiv},
  pages = {2023--11},
  year = {2023},
  publisher = {Cold Spring Harbor Laboratory},
}

A Bayesian method to cluster single-cell RNA sequencing data using copy number alterations

Salvatore Milite, Riccardo Bergamin, Lucrezia Patruno, and 2 more authors

Bioinformatics, 2022

Bib

@article{milite2022bayesian,
  title = {A Bayesian method to cluster single-cell RNA sequencing data using copy number alterations},
  author = {Milite, Salvatore and Bergamin, Riccardo and Patruno, Lucrezia and Calonaci, Nicola and Caravagna, Giulio},
  journal = {Bioinformatics},
  volume = {38},
  number = {9},
  pages = {2512--2518},
  year = {2022},
  publisher = {Oxford University Press},
}