Publikation:

An improved constraint filtering technique for inferring hidden states and parameters of a biological model

Vorschaubild

Dateien

Zu diesem Dokument gibt es keine Dateien.

Datum

2013

Autor:innen

Murtuza Baker, Syed
Poskar, C. Hart
Junker, Björn H.

Herausgeber:innen

Kontakt

ISSN der Zeitschrift

Electronic ISSN

ISBN

Bibliografische Daten

Verlag

Schriftenreihe

Auflagebezeichnung

URI (zitierfähiger Link)
DOI (zitierfähiger Link)
https://doi.org/10.1093/bioinformatics/btt097
ArXiv-ID

Internationale Patentnummer

Angaben zur Forschungsförderung

Projekt

Open Access-Veröffentlichung

Sammlungen

Informatik und Informationswissenschaft: Publikationen
Core Facility der Universität Konstanz

Gesperrt bis

Titel in einer weiteren Sprache

Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published

Erschienen in

Bioinformatics. 2013, 29(8), pp. 1052-1059. ISSN 1367-4803. eISSN 1460-2059. Available under: doi: 10.1093/bioinformatics/btt097

Zusammenfassung

In systems biology, kinetic models represent the biological system using a set of ordinary differential equations (ODEs). The correct values of the parameters within these ODEs are critical for a reliable study of the dynamic behaviour of such systems. Typically, it is only possible to experimentally measure a fraction of these parameter values. The rest must be indirectly determined from measurements of other quantities. In this article, we propose a novel statistical inference technique to computationally estimate these unknown parameter values. By characterizing the ODEs with non-linear state-space equations, this inference technique models the unknown parameters as hidden states, which can then be estimated from noisy measurement data.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
004 Informatik

Schlagwörter

Konferenz

Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690MURTUZA BAKER, Syed, C. Hart POSKAR, Falk SCHREIBER, Björn H. JUNKER, 2013. An improved constraint filtering technique for inferring hidden states and parameters of a biological model. In: Bioinformatics. 2013, 29(8), pp. 1052-1059. ISSN 1367-4803. eISSN 1460-2059. Available under: doi: 10.1093/bioinformatics/btt097
BibTex
@article{MurtuzaBaker2013-04-15impro-38241,
  year={2013},
  doi={10.1093/bioinformatics/btt097},
  title={An improved constraint filtering technique for inferring hidden states and parameters of a biological model},
  number={8},
  volume={29},
  issn={1367-4803},
  journal={Bioinformatics},
  pages={1052--1059},
  author={Murtuza Baker, Syed and Poskar, C. Hart and Schreiber, Falk and Junker, Björn H.}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/38241">
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-03-31T09:22:07Z</dcterms:available>
    <dc:language>eng</dc:language>
    <dcterms:abstract xml:lang="eng">In systems biology, kinetic models represent the biological system using a set of ordinary differential equations (ODEs). The correct values of the parameters within these ODEs are critical for a reliable study of the dynamic behaviour of such systems. Typically, it is only possible to experimentally measure a fraction of these parameter values. The rest must be indirectly determined from measurements of other quantities. In this article, we propose a novel statistical inference technique to computationally estimate these unknown parameter values. By characterizing the ODEs with non-linear state-space equations, this inference technique models the unknown parameters as hidden states, which can then be estimated from noisy measurement data.</dcterms:abstract>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-03-31T09:22:07Z</dc:date>
    <dc:contributor>Poskar, C. Hart</dc:contributor>
    <dc:creator>Schreiber, Falk</dc:creator>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:contributor>Murtuza Baker, Syed</dc:contributor>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/38241"/>
    <dc:creator>Murtuza Baker, Syed</dc:creator>
    <dc:creator>Poskar, C. Hart</dc:creator>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:contributor>Schreiber, Falk</dc:contributor>
    <dcterms:title>An improved constraint filtering technique for inferring hidden states and parameters of a biological model</dcterms:title>
    <dc:creator>Junker, Björn H.</dc:creator>
    <dcterms:issued>2013-04-15</dcterms:issued>
    <dc:contributor>Junker, Björn H.</dc:contributor>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
  </rdf:Description>
</rdf:RDF>

Interner Vermerk

xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter

Kontakt
URL der Originalveröffentl.

Prüfdatum der URL

Prüfungsdatum der Dissertation

Finanzierungsart

Kommentar zur Publikation

Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Nein
Begutachtet
Diese Publikation teilen