Propagating semantic information in biochemical network models.

ABSTRACT:

Background

To enable automatic searches, alignments, and model combination, the elements of systems biology models need to be compared and matched across models. Elements can be identified by machine-readable biological annotations, but assigning such annotations and matching non-annotated elements is tedious work and calls for automation.

Results

A new method called "semantic propagation" allows the comparison of model elements based not only on their own annotations, but also on annotations of surrounding elements in the network. One may either propagate feature vectors, describing the annotations of individual elements, or quantitative similarities between elements from different models. Based on semantic propagation, we align partially annotated models and find annotatio

SUBMITTER: Schulz M 

PROVIDER: S-EPMC3340317 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature