SNIC
SUPR
SNIC SUPR
Deep learning for protein prediction
Dnr:

SNIC 2018/1-26

Type:

SNAC Large

Principal Investigator:

Arne Elofsson

Affiliation:

Stockholms universitet

Start Date:

2018-07-01

End Date:

2019-07-01

Primary Classification:

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

Secondary Classification:

10610: Bioinformatics and Systems Biology (methods development to be 10203)

Tertiary Classification:

10601: Structural Biology

Allocation

Abstract

Machine Learning has had profound impact on life-science, as well as many other scientific areas. Lately, deep learning strategies have shown great progress in areas such as speech and image recognition. Here, these methods clearly outperform earlier machine learning methods. Deep learning methods are also starting to make an impact in life science, but adaptation has been slow. We believe a much wider life science community can start using these tools - and that the impact of this might be significant. We have a long history in developing widely adapted bioinformatics methods, primarily within the area of protein structure prediction. These methods have been based on deep biological insights and various machine learning metods, including deep learning. Here, we apply for computational resource to continue this development.