BIROn - Birkbeck Institutional Research Online

    Using Deep Maxout Neural Networks to improve the accuracy of function prediction from Protein Interaction Networks

    Wan, Cen and Cozzetto, D. and Fa, R. and Jones, D. (2019) Using Deep Maxout Neural Networks to improve the accuracy of function prediction from Protein Interaction Networks. PLoS One , ISSN 1932-6203.

    [img]
    Preview
    Text
    PLOSONE.pdf - Published Version of Record
    Available under License Creative Commons Attribution.

    Download (3MB) | Preview

    Abstract

    Protein-protein interaction network data provides valuable information that infers direct links between genes and their biological roles. This information brings a fundamental hypothesis for protein function prediction that interacting proteins tend to have similar functions. With the help of recently-developed network embedding feature generation methods and deep maxout neural networks, it is possible to extract functional representations that encode direct links between protein-protein interactions information and protein function. Our novel method, STRING2GO, successfully adopts deep maxout neural networks to learn functional representations simultaneously encoding both protein-protein interactions and functional predictive information. The experimental results show that STRING2GO outperforms other protein-protein interaction network-based prediction methods and one benchmark method adopted in a recent large scale protein function prediction competition.

    Metadata

    Item Type: Article
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Depositing User: Cen Wan
    Date Deposited: 23 Oct 2019 17:46
    Last Modified: 09 Aug 2023 12:47
    URI: https://eprints.bbk.ac.uk/id/eprint/29618

    Statistics

    Activity Overview
    6 month trend
    200Downloads
    6 month trend
    138Hits

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item Edit/View Item