Searching remote homology with spectral clustering with symmetry in neighborhood cluster kernels.

ABSTRACT:

Unlabelled

Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of "recent" paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsu

SUBMITTER: Maulik U 

PROVIDER: S-EPMC3574063 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature