<p>Cancer signatures for reproducible gene expression analysis data: the computational way to achieve precision medicine</p>

Stefania Pirrotta; Laura Masatti; Fabiola Pedrini; Chiara Romualdi; Enrica Calura

doi:10.7490/f1000research.1119106.1

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Pirrotta S, Masatti L, Pedrini F et al. Cancer signatures for reproducible gene expression analysis data: the computational way to achieve precision medicine [version 1; not peer reviewed]. F1000Research 2022, 11:998 (poster) (https://doi.org/10.7490/f1000research.1119106.1)

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Cancer signatures for reproducible gene expression analysis data: the computational way to achieve precision medicine

Stefania Pirrotta¹, Laura Masatti, Fabiola Pedrini, Chiara Romualdi, Enrica Calura

Published 06 Sep 2022 (https://doi.org/10.7490/f1000research.1119106.1)

Author Affiliations

¹ University of Padova, Italy

Copyright © 2022 Pirrotta S 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 06 Sep 2022

Cancer signatures for reproducible gene expression analysis data: the computational way to achieve precision medicine
[version 1; not peer reviewed]

Stefania Pirrotta¹, Laura Masatti, Fabiola Pedrini, Chiara Romualdi, Enrica Calura

Author Affiliations

¹ University of Padova, Italy

Presented at

EuroBioC 2022

Abstract

Competing Interests

No competing interests were disclosed

Keywords

signature, cancer, gene expression

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