Supervised maximum-likelihood weighting of composite protein networks for complex prediction.

ABSTRACT:

Background

Protein complexes participate in many important cellular functions, so finding the set of existent complexes is essential for understanding the organization and regulation of processes in the cell. With the availability of large amounts of high-throughput protein-protein interaction (PPI) data, many algorithms have been proposed to discover protein complexes from PPI networks. However, such approaches are hindered by the high rate of noise in high-throughput PPI data, including spurious and missing interactions. Furthermore, many transient interactions are detected between proteins that are not from the same complex, while not all proteins from the same complex may actually interact. As a result, predicted complexes often do not match true complexes well, and many true c

SUBMITTER: Yong CH 

PROVIDER: S-EPMC3521185 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature