<p>An automatic machine learning tool for prediction of immune-evasion mechanisms in TCGA cancer samples</p>

Andreia Rogerio; Claudia Antunes; Anita Grigoriadis; Jelmar Quist

doi:10.7490/f1000research.1117397.1

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Rogerio A, Antunes C, Grigoriadis A and Quist J. An automatic machine learning tool for prediction of immune-evasion mechanisms in TCGA cancer samples [version 1; not peer reviewed]. F1000Research 2019, 8(ISCB Comm J):1557 (poster) (https://doi.org/10.7490/f1000research.1117397.1)

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An automatic machine learning tool for prediction of immune-evasion mechanisms in TCGA cancer samples

Andreia Rogerio¹, Claudia Antunes, Anita Grigoriadis, Jelmar Quist

Published 01 Sep 2019 (https://doi.org/10.7490/f1000research.1117397.1)

Author Affiliations

¹ University of Lisbon, Portugal

Copyright © 2019 Rogerio A 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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CITE

Published 01 Sep 2019

An automatic machine learning tool for prediction of immune-evasion mechanisms in TCGA cancer samples
[version 1; not peer reviewed]

Andreia Rogerio¹, Claudia Antunes, Anita Grigoriadis, Jelmar Quist

Author Affiliations

¹ University of Lisbon, Portugal

Presented at

ISMB/ECCB 2019

Abstract

Competing Interests

No competing interests were disclosed

Keywords

cancer, immunology, immune evasion, immunotherapy, machine learning

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