Predicting protein-protein interactions from primary protein sequences using a novel multi-scale local feature representation scheme and the random forest.

ABSTRACT: The study of protein-protein interactions (PPIs) can be very important for the understanding of biological cellular functions. However, detecting PPIs in the laboratories are both time-consuming and expensive. For this reason, there has been much recent effort to develop techniques for computational prediction of PPIs as this can complement laboratory procedures and provide an inexpensive way of predicting the most likely set of interactions at the entire proteome scale. Although much progress has already been achieved in this direction, the problem is still far from being solved. More effective approaches are still required to overcome the limitations of the current ones. In this study, a novel Multi-scale Local Descriptor (MLD) feature representation scheme is proposed to extract feature

SUBMITTER: You ZH 

PROVIDER: S-EPMC4422660 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature