Compressive Kalman filtering for recovering temporally-rewiring genetic networks

Jehandad Khan, Nidhal Bouaynaya, Hassan M. Fathallah-Shaykh

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Genetic regulatory networks undergo rewiring over time in response to cellular developments and environmental stimuli. The main challenge in estimating time-varying genetic interactions is the limited number of observations at each time point; thus making the problem unidentifiable. We formulate the recovery of temporally-rewiring genetic networks as a tracking problem, where the target to be tracked over time consists of the set of genetic interactions. We circumvent the observability issue (due to the limited number of measurements) by taking into account the sparsity of genetic networks. With linear dynamics, we use a compressive Kalman filter to track the interactions as they evolve over time. Our simulation results show that the compressive Kalman filter achieves good tracking performance even with one measurement available at each time point; whereas the classical (unconstrained) Kalman filter completely fails in obtaining meaningful tracking.

    Original languageEnglish (US)
    Title of host publication2013 Proceedings of the 21st European Signal Processing Conference, EUSIPCO 2013
    PublisherEuropean Signal Processing Conference, EUSIPCO
    ISBN (Print)9780992862602
    StatePublished - Jan 1 2013
    Event2013 21st European Signal Processing Conference, EUSIPCO 2013 - Marrakech, Morocco
    Duration: Sep 9 2013Sep 13 2013

    Publication series

    NameEuropean Signal Processing Conference

    Other

    Other2013 21st European Signal Processing Conference, EUSIPCO 2013
    Country/TerritoryMorocco
    CityMarrakech
    Period9/9/139/13/13

    ASJC Scopus subject areas

    • Signal Processing
    • Electrical and Electronic Engineering

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