Synthesis of the Dynamical Properties of Feedback Loops in Bio-pathways.

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ID: 20387
2019
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Ranked #3 of 27 articles by views in ieee/acm transactions on computational biology and bioinformatics

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Abstract
Feedback loops regulate various biological functions such as oscillations, bistability and robustness. They play a significant role in developmental signalling and failure of feedback can lead to disease. Systematic analysis of feedback loops could be useful in understanding their properties and biological effects. We propose here a method to automatically analyze feedback loops in bio-pathways and synthesize temporal logic properties which describe their dynamics. Starting with an ordinary differential equations (ODEs) based model of a bio-pathway, for a chosen feedback loop present in the pathway, we use a convolutional neural network to classify the behaviour of the key components of the feedback according to templates specified in bounded linear temporal logic (BLTL). Once a template has been identified, we instantiate the symbolic variables appearing in the template and synthesize properties using a parameter estimation procedure based on sequential hypothesis testing. We have applied this framework to a number of bio-pathway models and validated that the synthesized properties faithfully describe the behaviour of the feedback loops.
Reference Key
zhou2019synthesisieeeacm Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Zhou, Jun;Ramanathan, R;Wong, Weng-Fai;
Journal ieee/acm transactions on computational biology and bioinformatics
Year 2019
DOI
10.1109/TCBB.2019.2936200
URL
Keywords Keywords not found

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