SUPR
PON predictors
Dnr:

SNIC 2022/6-192

Type:

SNIC Medium Storage

Principal Investigator:

Mauno Vihinen

Affiliation:

Lunds universitet

Start Date:

2022-08-17

End Date:

2023-09-01

Primary Classification:

10203: Bioinformatics (Computational Biology) (applications to be 10610)

Allocation

  • Centrestorage nobackup at LUNARC: 10000 GiB

Abstract

Development of AI methods for variant interpretation, i.e. detecting which variants, typically genetic alterations, are likely disease-causing and which are benign. Methods are based on extensively selected high-quality datasets of experimentally validated cases. Storage capacity is needed for calculation of some features, especially evolutionary conservation based on ratios of synonymous and non-synonymous variations in families of orthologous sequences. These are rather heavy and space-consuming calculations. The process has to be repeated once of twice per year as new orthologues are identified.