Network component analysis: reconstruction of regulatory signals in biological systems.

ABSTRACT: High-dimensional data sets generated by high-throughput technologies, such as DNA microarray, are often the outputs of complex networked systems driven by hidden regulatory signals. Traditional statistical methods for computing low-dimensional or hidden representations of these data sets, such as principal component analysis and independent component analysis, ignore the underlying network structures and provide decompositions based purely on a priori statistical constraints on the computed component signals. The resulting decomposition thus provides a phenomenological model for the observed data and does not necessarily contain physically or biologically meaningful signals. Here, we develop a method, called network component analysis, for uncovering hidden regulatory signals from outputs

SUBMITTER: Liao JC 

PROVIDER: S-EPMC307600 | biostudies-literature | 2003 Dec

REPOSITORIES: biostudies-literature