Statistical model comparison applied to common network motifs.

ABSTRACT:

Background

Network motifs are small modules that show interesting functional and dynamic properties, and are believed to be the building blocks of complex cellular processes. However, the mechanistic details of such modules are often unknown: there is uncertainty about the motif architecture as well as the functional form and parameter values when converted to ordinary differential equations (ODEs). This translates into a number of candidate models being compatible with the system under study. A variety of statistical methods exist for ranking models including maximum likelihood-based and Bayesian methods. Our objective is to show how such methods can be applied in a typical systems biology setting.

Results

We focus on four commonly occurring network motif structures and sho

SUBMITTER: Domedel-Puig N 

PROVIDER: S-EPMC2855527 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature