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
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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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
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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