{
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  "Package": "MSclassifR",
  "Type": "Package",
  "Title": "Automated Classification of Mass Spectra",
  "Version": "0.5.0",
  "Authors@R": "c(\nperson(\"Alexandre\", \"Godmer\", role = c(\"aut\", \"cre\"), email = \"alexandre.godmer@aphp.fr\"),\nperson(\"Quentin\", \"Giai Gianetto\", role = \"aut\", email = \"quentin.giaigianetto@pasteur.fr\"),\nperson(\"Karen\", \"Druart\", role = \"aut\")\n)",
  "Maintainer": "Alexandre Godmer <alexandre.godmer@aphp.fr>",
  "Description": "Functions to classify mass spectra in known categories and\nto determine discriminant mass-to-charge values (m/z). Includes\neasy-to-use preprocessing pipelines for Matrix Assisted Laser\nDesorption Ionisation - Time Of Flight Mass Spectrometry\n(MALDI-TOF) mass spectra, methods to select discriminant m/z\nfrom labelled libraries, and tools to predict categories\n(species, phenotypes, etc.) from selected features. Also\nprovides utilities to build design matrices from peak\nintensities and labels. While this package was developed with\nthe aim of identifying very similar species or phenotypes of\nbacteria from MALDI-TOF MS, the functions of this package can\nalso be used to classify other categories associated to mass\nspectra; or from mass spectra obtained with other mass\nspectrometry techniques. Parallelized processing and optional\nC++-accelerated functions are available (notably to deal with\nlarge datasets) from version 0.5.0.  If you use this package in\nyour research, please cite the associated publication\n(<doi:10.1016/j.eswa.2025.128796>). For a comprehensive guide,\nadditional applications, and detailed examples, see\n<https://github.com/agodmer/MSclassifR_examples>.",
  "URL": "https://github.com/agodmer/MSclassifR_examples,\nhttps://doi.org/10.1016/j.eswa.2025.128796",
  "BugReports": "https://github.com/agodmer/MSclassifR_examples/issues",
  "License": "GPL (>= 3)",
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  "Author": "Alexandre Godmer [aut, cre], Quentin Giai Gianetto [aut], Karen\nDruart [aut]",
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  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2025-12-09 13:07:46 UTC",
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