Machine learning for microbiomes

Dnr:

SNIC 2017/7-86

Type:

SNAC Small

Principal Investigator:

Anders Andersson

Affiliation:

Kungliga Tekniska högskolan

Start Date:

2017-05-19

End Date:

2018-06-01

Primary Classification:

10203: Bioinformatik (beräkningsbiologi) (tillämpningar under 10610)

Webpage:

http://envgen.github.io/

Allocation

Abstract

Using environmental DNA to measure a wide range of environmental conditions is a new research direction of genetics and environmental science. In this project, we plan to investigate how marine metagenome data sampled from the Baltic Sea can be used to predict and monitor environmental conditions. Various machine learning approaches will be evaluated for the ability to predict environmental conditions from the metagenomes data.