Network motif-based identification of transcription factor-target gene relationships by integrating multi-source biological data.

ABSTRACT:

Background

Integrating data from multiple global assays and curated databases is essential to understand the spatio-temporal interactions within cells. Different experiments measure cellular processes at various widths and depths, while databases contain biological information based on established facts or published data. Integrating these complementary datasets helps infer a mutually consistent transcriptional regulatory network (TRN) with strong similarity to the structure of the underlying genetic regulatory modules. Decomposing the TRN into a small set of recurring regulatory patterns, called network motifs (NM), facilitates the inference. Identifying NMs defined by specific transcription factors (TF) establishes the framework structure of a TRN and allows the inference of TF-t

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC2386822 | biostudies-literature | 2008 Apr

REPOSITORIES: biostudies-literature