Analyzing differential regulatory networks modulated by continuous-state genomic features in glioblastoma multiforme

Yu Chiao Chiu, Kai Wen Liang, Tzu Hung Hsiao, Yidong Chen, Eric Y. Chuang

    Producción científica: Conference contribution

    1 Cita (Scopus)

    Resumen

    Gene regulatory networks are a global representation of complex interactions between molecules that dictate cellular behavior. Study of a regulatory network modulated by single or multiple modulators' expression levels, including microRNAs (miRNAs) and transcription factors (TFs), in different conditions can further reveal the modulators' roles in diseases such as cancers. Existing computational methods for identifying such modulated regulatory networks are typically carried out by comparing groups of samples dichotomized with respect to the modulator status, ignoring the fact that most biological features are intrinsically continuous variables. Here we devised a sliding window-based regression scheme and proposed the Regression-based Inference of Modulation (RIM) algorithm to infer the dynamic gene regulation modulated by continuous-state modulators. We demonstrated the improvement in performance as well as computation efficiency achieved by RIM. Applying RIM to genome-wide expression profiles of 520 glioblastoma multiforme (GBM) tumors, we investigated miRNA-and TF-modulated gene regulatory networks and showed their association with dynamic cellular processes and brain-related functions in GBM. Overall, the proposed algorithm provides an efficient and robust scheme for comprehensively studying modulated gene regulatory networks.

    Idioma originalEnglish (US)
    Título de la publicación alojadaProceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
    Editoreslng. Matthieu Schapranow, Jiayu Zhou, Xiaohua Tony Hu, Bin Ma, Sanguthevar Rajasekaran, Satoru Miyano, Illhoi Yoo, Brian Pierce, Amarda Shehu, Vijay K. Gombar, Brian Chen, Vinay Pai, Jun Huan
    EditorialInstitute of Electrical and Electronics Engineers Inc.
    Páginas171-176
    Número de páginas6
    ISBN (versión digital)9781467367981
    DOI
    EstadoPublished - dic 16 2015
    EventoIEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015 - Washington, United States
    Duración: nov 9 2015nov 12 2015

    Serie de la publicación

    NombreProceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015

    Other

    OtherIEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
    País/TerritorioUnited States
    CiudadWashington
    Período11/9/1511/12/15

    ASJC Scopus subject areas

    • Software
    • Artificial Intelligence
    • Health Informatics
    • Biomedical Engineering

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