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Mining Plausible Patterns from Genomic Data

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F06%3A00119833" target="_blank" >RIV/68407700:21230/06:00119833 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Mining Plausible Patterns from Genomic Data

  • Original language description

    The discovery of biologically interpretable knowledge from gene expression data is one of the largest contemporary genomic challenges. As large volumes of expression data are being generated, there is a great need for automated tools that provide the means to analyze them. However, the same tools can provide an overwhelming number of candidate hypotheses which can hardly be manually exploited by an expert. An additional knowledge helping to focus automatically on the most plausible candidates only can up-value the experiment significantly. Background knowledge available in literature databases, biological ontologies and other sources can be used for this purpose. In this paper we propose and verify a methodology that enables to effectively mine and represent meaningful over-expression patterns. Each pattern represents a bi-set of a gene group over-expressed in a set of biological situations.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JC - Computer hardware and software

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/1ET101210513" target="_blank" >1ET101210513: Relational machine learning for analysis of biomedical data</a><br>

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2006

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of Nineteenth IEEE International Symposium on Computer-Based Medical Systems

  • ISBN

    978-0-7695-2517-4

  • ISSN

    1063-7125

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    183-188

  • Publisher name

    IEEE Computer Society Press

  • Place of publication

    Los Alamitos

  • Event location

    Utah

  • Event date

    Jun 22, 2006

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article