Domain prediction with probabilistic directional context.

ABSTRACT:

Motivation

Protein domain prediction is one of the most powerful approaches for sequence-based function prediction. Although domain instances are typically predicted independently of each other, newer approaches have demonstrated improved performance by rewarding domain pairs that frequently co-occur within sequences. However, most of these approaches have ignored the order in which domains preferentially co-occur and have also not modeled domain co-occurrence probabilistically.

Results

We introduce a probabilistic approach for domain prediction that models 'directional' domain context. Our method is the first to score all domain pairs within a sequence while taking their order into account, even for non-sequential domains. We show that our approach extends a previous Markov

SUBMITTER: Ochoa A 

PROVIDER: S-EPMC5870623 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature