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An empirical comparison of popular structure learning algorithms with a view to gene network inference

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00477168" target="_blank" >RIV/67985556:_____/17:00477168 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1016/j.ijar.2016.12.012" target="_blank" >http://dx.doi.org/10.1016/j.ijar.2016.12.012</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.ijar.2016.12.012" target="_blank" >10.1016/j.ijar.2016.12.012</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    An empirical comparison of popular structure learning algorithms with a view to gene network inference

  • Original language description

    In this work, we study the performance of different structure learning algorithms in the context of inferring gene networks from transcription data. We consider representatives of different structure learning approaches, some of which perform unrestricted searches, such as the PC algorithm and the Gobnilp method, and some of which introduce prior information on the structure, such as the K2 algorithm. Competing methods are evaluated both in terms of their predictive accuracy and their ability to reconstruct the true underlying network. Areal data application based on an experiment performed by the University of Padova is also considered.

  • 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

    <a href="/en/project/GA16-12010S" target="_blank" >GA16-12010S: Conditional independence structures: combinatorial and optimization methods</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2017

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    International Journal of Approximate Reasoning

  • ISSN

    0888-613X

  • e-ISSN

  • Volume of the periodical

    88

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    14

  • Pages from-to

    602-613

  • UT code for WoS article

    000407655600031

  • EID of the result in the Scopus database

    2-s2.0-85009223244