<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>614</id>
    <completedYear>2012</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>13</pageNumber>
    <edition/>
    <issue>72</issue>
    <volume>6</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Integrated pathway modules using time-course metabolic profiles and EST data from Milnesium tardigradum</title>
    <abstract language="eng">Tardigrades are multicellular organisms, resistant to extreme environmental changes such as heat, drought, radiation and freezing. They outlast these conditions in an inactive form (tun) to escape damage to cellular structures and cell death. Tardigrades are apparently able to prevent or repair such damage and are therefore a crucial model organism for stress tolerance. Cultures of the tardigrade Milnesium tardigradum were dehydrated by removing the surrounding water to induce tun formation. During this process and the subsequent rehydration, metabolites were measured in a time series by GC-MS. Additionally expressed sequence tags are available, especially libraries generated from the active and inactive state. The aim of this integrated analysis is to trace changes in tardigrade metabolism and identify pathways responsible for their extreme resistance against physical stress.</abstract>
    <parentTitle language="eng">BMC Systems Biology</parentTitle>
    <identifier type="issn">1752-0509</identifier>
    <identifier type="urn">urn:nbn:de:kobv:526-opus4-6146</identifier>
    <enrichment key="SourceTitle">Beisser et al.:Integrated pathway modules using time-course metabolic profiles and EST data from Milnesium tardigradum. BMC Systems Biology 2012 6:72.</enrichment>
    <enrichment key="DOI_VoR">https://doi.org/10.1186/1752-0509-6-72</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 2.0 Generic</licence>
    <author>Daniela Beisser</author>
    <author>Markus Grohme</author>
    <author>Joachim Kopka</author>
    <author>Marcus Frohme</author>
    <author>Ralph O. Schill</author>
    <author>Steffen Hengherr</author>
    <author>Thomas Dandekar</author>
    <author>Gunnar W. Klau</author>
    <author>Marcus Dittrich</author>
    <author>Tobias Müller</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>integrated network analysis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>functional module</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>metabolic profile</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>metabolic pathway</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>trend test</value>
    </subject>
    <collection role="ddc" number="570">Biowissenschaften; Biologie</collection>
    <collection role="institutes" number="">Fachbereich Ingenieurwesen / Wirtschaftsingenieurwesen (bis 8/2014)</collection>
    <collection role="open_access" number="">open_access</collection>
    <collection role="green_open_access" number="1">Gold Open Access</collection>
    <thesisPublisher>Technische Hochschule Wildau</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-th-wildau/files/614/2F1752-0509-6-72.pdf</file>
  </doc>
</export-example>
