Publikation:

Deducing intracellular distributions of metabolic pathways from genomic data

Lade...
Vorschaubild

Dateien

Gruber_258202.pdf
Gruber_258202.pdfGröße: 8.62 MBDownloads: 840

Datum

2014

Herausgeber:innen

Kontakt

ISSN der Zeitschrift

Electronic ISSN

ISBN

Bibliografische Daten

Verlag

Schriftenreihe

Auflagebezeichnung

ArXiv-ID

Internationale Patentnummer

Angaben zur Forschungsförderung

Projekt

Open Access-Veröffentlichung
Open Access Green
Core Facility der Universität Konstanz

Gesperrt bis

Titel in einer weiteren Sprache

Publikationstyp
Beitrag zu einem Sammelband
Publikationsstatus
Published

Erschienen in

SRIRAM, Ganesh, ed.. Plant Metabolism. Totowa, NJ: Humana Press, 2014, pp. 187-211. Methods in Molecular Biology. 1083. ISBN 978-1-62703-660-3. Available under: doi: 10.1007/978-1-62703-661-0_12

Zusammenfassung

In the recent years, a large number of genomes from a variety of different organisms have been sequenced. Most of the sequence data has been publicly released and can be assessed by interested users. However, this wealth of information is currently underexploited by scientists not directly involved in genome annotation. This is partially because sequencing, assembly, and automated annotation can be done much faster than the identification, classification, and prediction of the intracellular localization of the gene products. This part of the annotation process still largely relies on manual curation and addition of contextual information. Users of genome databases who are unfamiliar with the types of data available from (whole) genomes might therefore find themselves either overwhelmed by the vast amount and multiple layers of data or dissatisfied with less-than-meaningful analyses of the data.
In this chapter we present procedures and approaches to identify and characterize gene models of enzymes involved in metabolic pathways based on their similarity to known sequences. Furthermore we describe how to predict the subcellular location of the proteins using publicly available prediction servers and how to interpret the obtained results. The strategies we describe are generally applicable to organisms with primary plastids such as land plants or green algae. Additionally, we describe strategies suitable for those groups of algae with secondary plastids (for instance diatoms), which are characterized by a different cellular topology and a larger number of intracellular compartments compared to plants.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
570 Biowissenschaften, Biologie

Schlagwörter

Metabolic pathways, subcellular localization, presequences, algae, diatoms

Konferenz

Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690GRUBER, Ansgar, Peter G. KROTH, 2014. Deducing intracellular distributions of metabolic pathways from genomic data. In: SRIRAM, Ganesh, ed.. Plant Metabolism. Totowa, NJ: Humana Press, 2014, pp. 187-211. Methods in Molecular Biology. 1083. ISBN 978-1-62703-660-3. Available under: doi: 10.1007/978-1-62703-661-0_12
BibTex
@incollection{Gruber2014Deduc-25820,
  year={2014},
  doi={10.1007/978-1-62703-661-0_12},
  title={Deducing intracellular distributions of metabolic pathways from genomic data},
  number={1083},
  isbn={978-1-62703-660-3},
  publisher={Humana Press},
  address={Totowa, NJ},
  series={Methods in Molecular Biology},
  booktitle={Plant Metabolism},
  pages={187--211},
  editor={Sriram, Ganesh},
  author={Gruber, Ansgar and Kroth, Peter G.}
}
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/123456789/25820">
    <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/25820"/>
    <dc:contributor>Kroth, Peter G.</dc:contributor>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/25820/2/Gruber_258202.pdf"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2014-01-13T11:05:16Z</dc:date>
    <dcterms:abstract xml:lang="eng">In the recent years, a large number of genomes from a variety of different organisms have been sequenced. Most of the sequence data has been publicly released and can be assessed by interested users. However, this wealth of information is currently underexploited by scientists not directly involved in genome annotation. This is partially because sequencing, assembly, and automated annotation can be done much faster than the identification, classification, and prediction of the intracellular localization of the gene products. This part of the annotation process still largely relies on manual curation and addition of contextual information. Users of genome databases who are unfamiliar with the types of data available from (whole) genomes might therefore find themselves either overwhelmed by the vast amount and multiple layers of data or dissatisfied with less-than-meaningful analyses of the data.&lt;br /&gt;In this chapter we present procedures and approaches to identify and characterize gene models of enzymes involved in metabolic pathways based on their similarity to known sequences. Furthermore we describe how to predict the subcellular location of the proteins using publicly available prediction servers and how to interpret the obtained results. The strategies we describe are generally applicable to organisms with primary plastids such as land plants or green algae. Additionally, we describe strategies suitable for those groups of algae with secondary plastids (for instance diatoms), which are characterized by a different cellular topology and a larger number of intracellular compartments compared to plants.</dcterms:abstract>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/25820/2/Gruber_258202.pdf"/>
    <dcterms:title>Deducing intracellular distributions of metabolic pathways from genomic data</dcterms:title>
    <dcterms:bibliographicCitation>Plant Metabolism : Methods and Protocols / Ganesh Sriram (ed.). - Totowa, NJ : Humana Press, 2014. - S. 187-211. - (Methods in Molecular Biology, Methods and Protocols ; 1083). - ISBN 978-162-703-660-3</dcterms:bibliographicCitation>
    <dcterms:issued>2014</dcterms:issued>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2014-01-13T11:05:16Z</dcterms:available>
    <dc:language>eng</dc:language>
    <dc:creator>Kroth, Peter G.</dc:creator>
    <dc:rights>terms-of-use</dc:rights>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
    <dc:creator>Gruber, Ansgar</dc:creator>
    <dc:contributor>Gruber, Ansgar</dc:contributor>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
  </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
Ja
Begutachtet
Diese Publikation teilen