Interpreting protein abundance in Saccharomyces cerevisiae through relational learning.

ABSTRACT:

Motivation

Proteomic profiles reflect the functional readout of the physiological state of an organism. An increased understanding of what controls and defines protein abundances is of high scientific interest. Saccharomyces cerevisiae is a well-studied model organism, and there is a large amount of structured knowledge on yeast systems biology in databases such as the Saccharomyces Genome Database, and highly curated genome-scale metabolic models like Yeast8. These datasets, the result of decades of experiments, are abundant in information, and adhere to semantically meaningful ontologies.

Results

By representing this knowledge in an expressive Datalog database we generated data descriptors using relational learning that, when combined with supervised machine learning, enab

SUBMITTER: Brunnsaker D 

PROVIDER: S-EPMC10868306 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature