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Exploring attractor bifurcations in Boolean networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F22%3A00125836" target="_blank" >RIV/00216224:14330/22:00125836 - isvavai.cz</a>

  • Result on the web

    <a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-022-04708-9" target="_blank" >https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-022-04708-9</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1186/s12859-022-04708-9" target="_blank" >10.1186/s12859-022-04708-9</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Exploring attractor bifurcations in Boolean networks

  • Original language description

    Background Boolean networks (BNs) provide an effective modelling formalism for various complex biochemical phenomena. Their long term behaviour is represented by attractors–subsets of the state space towards which the BN eventually converges. These are then typically linked to different biological phenotypes. Depending on various logical parameters, the structure and quality of attractors can undergo a significant change, known as a bifurcation. We present a methodology for analysing bifurcations in asynchronous parametrised Boolean networks. Results In this paper, we propose a computational framework employing advanced symbolic graph algorithms that enable the analysis of large networks with hundreds of Boolean variables. To visualise the results of this analysis, we developed a novel interactive presentation technique based on decision trees, allowing us to quickly uncover parameters crucial to the changes in the attractor landscape. As a whole, the methodology is implemented in our tool AEON. We evaluate the method’s applicability on a complex human cell signalling network describing the activity of type-1 interferons and related molecules interacting with SARS-COV-2 virion. In particular, the analysis focuses on explaining the potential suppressive role of the recently proposed drug molecule GRL0617 on replication of the virus. Conclusions The proposed method creates a working analogy to the concept of bifurcation analysis widely used in kinetic modelling to reveal the impact of parameters on the system’s stability. The important feature of our tool is its unique capability to work fast with large-scale networks with a relatively large extent of unknown information. The results obtained in the case study are in agreement with the recent biological findings.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    BMC Bioinformatics

  • ISSN

    1471-2105

  • e-ISSN

  • Volume of the periodical

    23

  • Issue of the periodical within the volume

    173

  • Country of publishing house

    CH - SWITZERLAND

  • Number of pages

    18

  • Pages from-to

    1-18

  • UT code for WoS article

    000793836800001

  • EID of the result in the Scopus database

    2-s2.0-85130638799