Isofunctional Protein Subfamily Detection Using Data Integration and Spectral Clustering.

ABSTRACT: As increasingly more genomes are sequenced, the vast majority of proteins may only be annotated computationally, given experimental investigation is extremely costly. This highlights the need for computational methods to determine protein functions quickly and reliably. We believe dividing a protein family into subtypes which share specific functions uncommon to the whole family reduces the function annotation problem's complexity. Hence, this work's purpose is to detect isofunctional subfamilies inside a family of unknown function, while identifying differentiating residues. Similarity between protein pairs according to various properties is interpreted as functional similarity evidence. Data are integrated using genetic programming and provided to a spectral clustering algorithm, which c

SUBMITTER: Boari de Lima E 

PROVIDER: S-EPMC4922564 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature