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@ARTICLE{Eiteneuer:906828,
      author       = {Eiteneuer, Constantin and Velasco, David and Atemia, Joseph
                      and Wang, Dan and Schwacke, Rainer and Wahl, Vanessa and
                      Schrader, Andrea and Reimer, Julia J. and Fahrner, Sven and
                      Pieruschka, Roland and Schurr, Ulrich and Usadel, Björn and
                      Hallab, Asis},
      title        = {{GXP}: {A}nalyze and {P}lot {P}lant {O}mics {D}ata in {W}eb
                      {B}rowsers},
      journal      = {Plants},
      volume       = {11},
      number       = {6},
      issn         = {2223-7747},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2022-01722},
      pages        = {745 -},
      year         = {2022},
      abstract     = {Next-generation sequencing and metabolomics have become
                      very cost and work efficient and are integrated into an
                      ever-growing number of life science research projects.
                      Typically, established software pipelines analyze raw data
                      and produce quantitative data informing about gene
                      expression or concentrations of metabolites. These results
                      need to be visualized and further analyzed in order to
                      support scientific hypothesis building and identification of
                      underlying biological patterns. Some of these tools already
                      exist, but require installation or manual programming. We
                      developed “Gene Expression Plotter” (GXP), an RNAseq and
                      Metabolomics data visualization and analysis tool entirely
                      running in the user’s web browser, thus not needing any
                      custom installation, manual programming or uploading of
                      confidential data to third party servers. Consequently, upon
                      receiving the bioinformatic raw data analysis of RNAseq or
                      other omics results, GXP immediately enables the user to
                      interact with the data according to biological questions by
                      performing knowledge-driven, in-depth data analyses and
                      candidate identification via visualization and data
                      exploration. Thereby, GXP can support and accelerate complex
                      interdisciplinary omics projects and downstream analyses.
                      GXP offers an easy way to publish data, plots, and analysis
                      results either as a simple exported file or as a custom
                      website. GXP is freely available on GitHub (see
                      introduction).},
      cin          = {IBG-2 / IBG-4},
      ddc          = {580},
      cid          = {I:(DE-Juel1)IBG-2-20101118 / I:(DE-Juel1)IBG-4-20200403},
      pnm          = {2171 - Biological and environmental resources for
                      sustainable use (POF4-217)},
      pid          = {G:(DE-HGF)POF4-2171},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:35336631},
      UT           = {WOS:000774316000001},
      doi          = {10.3390/plants11060745},
      url          = {https://juser.fz-juelich.de/record/906828},
}