SNIC
SUPR
SNIC SUPR
Usage of systems biology and deep learning for high-throughput omics
Dnr:

SNIC 2017/1-526

Type:

SNAC Medium

Principal Investigator:

Mika Gustafsson

Affiliation:

Linköpings universitet

Start Date:

2017-11-29

End Date:

2018-12-01

Primary Classification:

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

Allocation

Abstract

A common problem with associating gene variants to complex disease associated traits is power and multiple testing. We have used gene networks to incorporate functional relevance among gene variants, but has not lead to decision support systems. In this project we aim to integrate network information with deep learning utilizing genomics in millions of gene variants and 1000's of patients and integrating transcriptomics and gene networks. For this purpose we will need to use TENSORFLOW and the GPU architecture available at Kebnekaise.