<p>The importance of being unbiased: why protein structure and training setup are important for predicting novel pathogenic genetic variants</p>

Alexander Gress; Sebastian Keller; Vasily Ramensky; Olga V. Kalinina

doi:10.7490/f1000research.1117213.1

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Gress A, Keller S, Ramensky V and Kalinina OV. The importance of being unbiased: why protein structure and training setup are important for predicting novel pathogenic genetic variants [version 1; not peer reviewed]. F1000Research 2019, 8(ISCB Comm J):1282 (slides) (https://doi.org/10.7490/f1000research.1117213.1)

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The importance of being unbiased: why protein structure and training setup are important for predicting novel pathogenic genetic variants

Alexander Gress¹, Sebastian Keller, Vasily Ramensky, Olga V. Kalinina

Published 31 Jul 2019 (https://doi.org/10.7490/f1000research.1117213.1)

Author Affiliations

¹ Helmholtz Centre for Infection Research, Germany

Copyright © 2019 Gress 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 31 Jul 2019

The importance of being unbiased: why protein structure and training setup are important for predicting novel pathogenic genetic variants
[version 1; not peer reviewed]

Alexander Gress¹, Sebastian Keller, Vasily Ramensky, Olga V. Kalinina

Author Affiliations

¹ Helmholtz Centre for Infection Research, Germany

Presented at

ISMB/ECCB 2019

Abstract

Competing Interests

No competing interests were disclosed

Keywords

Pathogenicity predicition, machine learning, genetic variants, non-synonymous single nucleotide polymorphisms

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