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Patents in GC/LC-MS data evaluation

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Classification of GC/LC-MS data

Literature for GC-MS data evaluation

Literature for comprehensive GC-MS data evaluation


  • AMDIS user guide; W. Gary Mallard and Janiel Reed; [PDF]
  • An Integrated Method for Spectrum Extraction and Compound Identification from GC/MS Data; S. E. Stein; [PDF]



  • Most of useful information are from James D. Little - there are 8 papers [Link]
  • The Critical Evaluation of a Comprehensive Mass Spectral Library ;P. Ausloos, C. L. Clifton, S. G. Lias, A. I. Mikaya, S. E. Stein, and D. V. Tchekhovskoi; O. D. Sparkman,V. Zaikin, Damo Zhu; [PDF]
  • A Novel Approach of Retrieval of Mass Spectrum of Mixture; Feng Gan and Yizeng Liang [PDF]
  • Library Search of Mass Spectra with a New Matching Algorithm Based on Substructure Similarity; Feng Gan, Jia-hong Yang and Yi-zeng Liang [PDF]
  • Neural Network as a Pattern Recognition Tool in Spectroscopy; Cheng Kok Choi; Hong Kong Baptist University [LINK]
    Gives a nice overview about the most MS-SEARCH algorithms like (Probability Based Matching (PBM) method from McLafferty and D.B. Stauffer, similarity search, "dot product" search algorithm from S.E. Stein and D.R. Scott) and others.


GC Retention Indices

  • Making sense of nontarget compound data from GC-MS library searches; William P.Eckel
    [PDF] (Lee retention index)
  • New Design of the Algorithm for GC Retention Indices of Any Organic Compounds Precalculation from Their Physico-Chemical Constants; Igor G. Zenkevich; [PDF]
  • Building a Comprehensive, Evaluated Collection of GC Retention Indices from Literature Data; J.K.Klassen,S.E.Stein,I.G. Zenkevich [PDF]



  • From MS Data via Chemometrics to Chemical Structure Information; K.Varmuza; [PDF]
  • Clustering and Classification of Analytical Data; Barry K. Lavine; [PDF]
  • Applied Chemometrics: From Chemical Data to Relevant Information; K.Varmuza; [PDF]
  • The feasibility of latent variables applied to GC-MS data; F. Brakstad [Scirus]
  • Anwendung multivariater Methoden und künstlicher neuronaler Netze zur Klassifizierung von Spirituosen mittels Headspace-GC-MS-Kopplung; P. Kursawe [PDF]


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