Identification of functional connections in biological neural networks using dynamical Bayesian networks

Dong, Chaoyi and Yue, Hong (2016) Identification of functional connections in biological neural networks using dynamical Bayesian networks. IFAC-PapersOnLine, 49 (26). pp. 178-183. ISSN 1474-6670 (https://doi.org/10.1016/j.ifacol.2016.12.122)

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Abstract

Investigation of the underlying structural characteristics and network properties of biological networks is crucial to understanding the system-level regulatory mechanism of network behaviors. A Dynamic Bayesian Network (DBN) identification method is developed based on the Minimum Description Length (MDL) to identify and locate functional connections among Pulsed Neural Networks (PNN), which are typical in synthetic biological networks. A score of MDL is evaluated for each candidate network structure which includes two factors: i) the complexity of the network; and ii) the likelihood of the network structure based on network dynamic response data. These two factors are combined together to determine the network structure. The DBN is then used to analyze the time-series data from the PNNs, thereby discerning causal connections which collectively show the network structures. Numerical studies on PNN with different number of nodes illustrate the effectiveness of the proposed strategy in network structure identification.

ORCID iDs

Dong, Chaoyi and Yue, Hong ORCID logoORCID: https://orcid.org/0000-0003-2072-6223;
  • Item type:Article
    ID code:57826
    Dates:
    Date
    Event
    9 October 2016
    Published
    24 July 2016
    Accepted
    Keywords:pulsed neural networks, dynamic Bayesian networks, minimum description length, casual connection, synthetic biological networks, network structure identification, Electrical Engineering. Electronics Nuclear Engineering, Electrical and Electronic Engineering
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:16 Sep 2016 13:28
    Last modified:01 Nov 2023 10:44
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/57826
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