volume 9, issue 7, P1721-1737 2017
DOI: 10.18632/aging.101264
View full text
|
Sign up to set email alerts
|
Share

Abstract: Increasing age is a risk factor for many diseases; therefore developing pharmacological interventions that slow down ageing and consequently postpone the onset of many age-related diseases is highly desirable. In this work we analyse data from the DrugAge database, which contains chemical compounds and their effect on the lifespan of model organisms. Predictive models were built using the machine learning method random forests to predict whether or not a chemical compound will increase Caenorhabditis elegans’ …

Expand abstract

Search citation statements

Order By: Relevance

Citation Types

2
60
0

Paper Sections

0
0
0
0
0

Publication Types

0
0
0
0

Relationship

0
0

Authors

Journals