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    <identifier>10.57760/sciencedb.32011</identifier>
    <datestamp>2025-11-24T17:53:22Z</datestamp>
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  <dc:date>2025-11-24</dc:date>
  <dc:title>Multidimensional chromatographic fingerprint fusion with machine learning: Entropy-based feature evaluation for TCM quality marker discovery</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.32011</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This dataset is used for the mining and analysis processing of TLC and LC-HRMS data in the article. Based on the thin-layer chromatography and mass spectrometry analyses of 15 batches of prepared collagen solution and the transmission process. RGB represents the channel information of TLC data, and also includes the intensity corresponding to different Rf values. The data from LC-HRMS includes the intensity corresponding to different m/z values, as well as the intensity values at the retention time. At the same time, the data set also includes the codes used during the process.</dc:description>
  <dc:subject>Multidimensional data fusion; chromatography; entropy-based feature selection; quality evaluation; Fufang E’jiao Jiang</dc:subject>
  <dc:creator>She Gaimei</dc:creator>
  <dc:creator>Ma Jiamu</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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