An Automated Peak Identification/Calibration Procedure for High-Dimensional Protein Measures from Mass Spectrometers

93Citations
Citations of this article
35Readers
Mendeley users who have this article in their library.

Abstract

Discovery of "signature" protein profiles that distinguish disease states (eg, malignant, benign, and normal) is a key step towards translating recent advancements in proteomic technologies into clinical utilities. Protein data generated from mass spectrometers are, however, large in size and have complex features due to complexities in both biological specimens and interfering biochemical/physical processes of the measurement procedure. Making sense out of such high-dimensional complex data is challenging and necessitates the use of a systematic data analytic strategy. We propose here a data processing strategy for two major issues in the analysis of such mass-spectrometry-generated proteomic data: (1) separation of protein "signals" from background "noise" in protein intensity measurements and (2) calibration of protein mass/charge measurements across samples. We illustrate the two issues and the utility of the proposed strategy using data from a prostate cancer biomarker discovery project as an example.

Cite

CITATION STYLE

APA

Yasui, Y., McLerran, D., Adam, B. L., Winget, M., Thornquist, M., & Feng, Z. (2003). An Automated Peak Identification/Calibration Procedure for High-Dimensional Protein Measures from Mass Spectrometers. Journal of Biomedicine and Biotechnology, 2003(4), 242–248. https://doi.org/10.1155/S111072430320927X

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free