Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Machine Learning for Microbial Phenotype Prediction

Machine Learning for Microbial Phenotype Prediction

Feldbauer, Roman

Paperback

Series: Bestmasters

Anatomy & PhysiologyBiologyGeneral Mathematics

ISBN10: 3658143185
ISBN13: 9783658143183
Publisher: Springer Nature
Published: Jun 24 2016
Pages: 110
Weight: 0.35
Height: 0.27 Width: 5.83 Depth: 8.27
Language: English
This thesis presents a scalable, generic methodology for microbial phenotype prediction based on supervised machine learning, several models for biological and ecological traits of high relevance, and the deployment in metagenomic datasets. The results suggest that the presented prediction tool can be used to automatically annotate phenotypes in near-complete microbial genome sequences, as generated in large numbers in current metagenomic studies. Unraveling relationships between a living organism's genetic information and its observable traits is a central biological problem. Phenotype prediction facilitated by machine learning techniques will be a major step forward to creating biological knowledge from big data.

Also in

Biology

View All