Effusion: prediction of protein function from sequence similarity networks.

ABSTRACT:

Motivation

Critical evaluation of methods for protein function prediction shows that data integration improves the performance of methods that predict protein function, but a basic BLAST-based method is still a top contender. We sought to engineer a method that modernizes the classical approach while avoiding pitfalls common to state-of-the-art methods.

Results

We present a method for predicting protein function, Effusion, which uses a sequence similarity network to add context for homology transfer, a probabilistic model to account for the uncertainty in labels and function propagation, and the structure of the Gene Ontology (GO) to best utilize sparse input labels and make consistent output predictions. Effusion's model makes it practical to integrate rare experimental dat

SUBMITTER: Yunes JM 

PROVIDER: S-EPMC6361244 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature