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AEON.py: Python library for attractor analysis in asynchronous 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%3A00127100" target="_blank" >RIV/00216224:14330/22:00127100 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1093/bioinformatics/btac624" target="_blank" >https://doi.org/10.1093/bioinformatics/btac624</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1093/bioinformatics/btac624" target="_blank" >10.1093/bioinformatics/btac624</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    AEON.py: Python library for attractor analysis in asynchronous Boolean networks

  • Original language description

    AEON.py is a Python library for the analysis of the long-term behaviour in very large asynchronous Boolean networks. It provides significant computational improvements over the state-of-the-art methods for attractor detection. Furthermore, it admits the analysis of partially specified Boolean networks with uncertain update functions. It also includes techniques for identifying viable source-target control strategies and the assessment of their robustness with respect to parameter perturbations.

  • 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

    BIOINFORMATICS

  • ISSN

    1367-4803

  • e-ISSN

    1367-4811

  • Volume of the periodical

    38

  • Issue of the periodical within the volume

    21

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    3

  • Pages from-to

    4978-4980

  • UT code for WoS article

    000857476100001

  • EID of the result in the Scopus database

    2-s2.0-85141004669