BioS2Net: Holistic Structural and Sequential Analysis of Biomolecules Using a Deep Neural Network.

ABSTRACT: For decades, the rate of solving new biomolecular structures has been exceeding that at which their manual classification and feature characterisation can be carried out efficiently. Therefore, a new comprehensive and holistic tool for their examination is needed. Here we propose the Biological Sequence and Structure Network (BioS2Net), which is a novel deep neural network architecture that extracts both sequential and structural information of biomolecules. Our architecture consists of four main parts: (i) a sequence convolutional extractor, (ii) a 3D structure extractor, (iii) a 3D structure-aware sequence temporal network, as well as (iv) a fusion and classification network. We have evaluated our approach using two protein fold classification datasets. BioS2Net achieved a 95.4% mean cla

SUBMITTER: Roethel A 

PROVIDER: S-EPMC8954277 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature