De novo Prediction of Moonlighting Proteins Using Multimodal Deep Ensemble Learning.

ABSTRACT: Moonlighting proteins (MPs) are a special type of protein with multiple independent functions. MPs play vital roles in cellular regulation, diseases, and biological pathways. At present, very few MPs have been discovered by biological experiments. Due to the lack of data sample, computation-based methods to identify MPs are limited. Currently, there is no de-novo prediction method for MPs. Therefore, systematic research and identification of MPs are urgently required. In this paper, we propose a multimodal deep ensemble learning architecture, named MEL-MP, which is the first de novo computation model for predicting MPs. First, we extract four sequence-based features: primary protein sequence information, evolutionary information, physical and chemical properties, and secondar

SUBMITTER: Li Y 

PROVIDER: S-EPMC8019903 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature