Efficient α, β-motif finder for identification of phenotype-related functional modules.

ABSTRACT:

Background

Microbial communities in their natural environments exhibit phenotypes that can directly cause particular diseases, convert biomass or wastewater to energy, or degrade various environmental contaminants. Understanding how these communities realize specific phenotypic traits (e.g., carbon fixation, hydrogen production) is critical for addressing health, bioremediation, or bioenergy problems.

Results

In this paper, we describe a graph-theoretical method for in silico prediction of the cellular subsystems that are related to the expression of a target phenotype. The proposed (α, β)-motif finder approach allows for identification of these phenotype-related subsystems that, in addition to metabolic subsystems, could include their regulators, sensors, transporters, and

SUBMITTER: Schmidt MC 

PROVIDER: S-EPMC3287386 | biostudies-literature | 2011 Nov

REPOSITORIES: biostudies-literature