Datamining Methodology for LC-MALDI-MS Based Peptide Profiling

Title: Datamining Methodology for LC-MALDI-MS Based Peptide Profiling

Volume: 8 Issue: 8

Author(s): Hans-Dieter Zucht, Jens Lamerz, Valery Khamenia, Carsten Schiller, Annette Appel, Harald Tammen, Reto Crameri and Hartmut Selle

Affiliation:

Keywords: Datamining, Mass spectrometry, biomarker, clinical proteomics, peptidomics, disease pattern recognition

Abstract: This report will provide a brief overview of the application of data mining in proteomic peptide profiling used for medical biomarker research. Mass spectrometry based profiling of peptides and proteins is frequently used to distinguish disease from non-disease groups and to monitor and predict drug effects. It has the promising potential to enter clinical laboratories as a general purpose diagnostic tool. Data mining methodologies support biomedical science to manage the vast data sets obtained from these instrumentations. Here we will review the typical workflow of peptide profiling, together with typical data mining methodology. Mass spectrometric experiments in peptidomics raise numerous questions in the fields of signal processing, statistics, experimental design and discriminant analysis.

Cite this article as:

Zucht Hans-Dieter, Lamerz Jens, Khamenia Valery, Schiller Carsten, Appel Annette, Tammen Harald, Crameri Reto and Selle Hartmut, Datamining Methodology for LC-MALDI-MS Based Peptide Profiling, Combinatorial Chemistry & High Throughput Screening 2005; 8 (8) . https://dx.doi.org/10.2174/138620705774962481