BIONIC: biological network integration using convolutions.

ABSTRACT: Biological networks constructed from varied data can be used to map cellular function, but each data type has limitations. Network integration promises to address these limitations by combining and automatically weighting input information to obtain a more accurate and comprehensive representation of the underlying biology. We developed a deep learning-based network integration algorithm that incorporates a graph convolutional network framework. Our method, BIONIC (Biological Network Integration using Convolutions), learns features that contain substantially more functional information compared to existing approaches. BIONIC has unsupervised and semisupervised learning modes, making use of available gene function annotations. BIONIC is scalable in both size and quantity of the input networ

SUBMITTER: Forster DT 

PROVIDER: S-EPMC11236286 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature