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Protein mass spectra data analysis for clinical biomarker discovery: a global review

Pascal Roy 1, 2 C. Truntzer 3 D. Maucort-Boulch 2 T. Jouve 2 Nicolas Molinari 4
2 Biostatistiques santé
Département biostatistiques et modélisation pour la santé et l'environnement [LBBE]
3 CLIPP - Plate-forme Protéomique CLIPP - Clinical and Innovation Proteomic Platform [Dijon]
FEMTO-ST - Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174), ICMUB - Institut de Chimie Moléculaire de l'Université de Bourgogne [Dijon]
Abstract : The identification of new diagnostic or prognostic biomarkers is one of the main aims of clinical cancer research. In recent years there has been a growing interest in using high throughput technologies for the detection of such biomarkers. In particular, mass spectrometry appears as an exciting tool with great potential. However, to extract any benefit from the massive potential of clinical proteomic studies, appropriate methods, improvement and validation are required. To better understand the key statistical points involved with such studies, this review presents the main data analysis steps of protein mass spectra data analysis, from the pre-processing of the data to the identification and validation of biomarker
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Pascal Roy, C. Truntzer, D. Maucort-Boulch, T. Jouve, Nicolas Molinari. Protein mass spectra data analysis for clinical biomarker discovery: a global review. Briefings in Bioinformatics, Oxford University Press (OUP), 2011, 12 (2), pp.176-186. ⟨10.1093/bib/bbq019⟩. ⟨hal-02645216⟩



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