<p>Simulate tumor microenvironment evolution from sequencing data through a hybrid multi-agent spatio-temporal model</p>

Giulia Cesaro; Mikele Milia; Giacomo Baruzzo; F Morandini; A Lazzarini; Piergiorgio Alotto; Noel Filipe  de Miranda; Zlatko Trajanoski; Francesca Finotello; Barbara Di Camillo

doi:10.7490/f1000research.1119314.1

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Cesaro G, Milia M, Baruzzo G et al. Simulate tumor microenvironment evolution from sequencing data through a hybrid multi-agent spatio-temporal model [version 1; not peer reviewed]. F1000Research 2022, 11:1503 (poster) (https://doi.org/10.7490/f1000research.1119314.1)

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Simulate tumor microenvironment evolution from sequencing data through a hybrid multi-agent spatio-temporal model

Giulia Cesaro, Mikele Milia, Giacomo Baruzzo, F Morandini, A Lazzarini, Piergiorgio Alotto, Noel Filipe de Miranda, Zlatko Trajanoski, Francesca Finotello, Barbara Di Camillo¹

Published 12 Dec 2022 (https://doi.org/10.7490/f1000research.1119314.1)

Author Affiliations

¹ Department of Information Engineering, University of Padova, 35131 Padova, Italy

Copyright © 2022 Cesaro G et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Published 12 Dec 2022

Simulate tumor microenvironment evolution from sequencing data through a hybrid multi-agent spatio-temporal model
[version 1; not peer reviewed]

Giulia Cesaro, Mikele Milia, Giacomo Baruzzo, F Morandini, A Lazzarini, Piergiorgio Alotto, Noel Filipe de Miranda, Zlatko Trajanoski, Francesca Finotello, Barbara Di Camillo¹

Author Affiliations

¹ Department of Information Engineering, University of Padova, 35131 Padova, Italy

Presented at

Bioinformatics and Computational Biology Conference (BBCC), 2022

Competing Interests

No competing interests were disclosed

Keywords

cancer, multi-agent model, simulation, omics data

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