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Peakbin Selection in Mass Spectrometry Data Using a Consensus Approach with Estimation of Distribution Algorithms

Published: 01 May 2011 Publication History

Abstract

Progress is continuously being made in the quest for stable biomarkers linked to complex diseases. Mass spectrometers are one of the devices for tackling this problem. The data profiles they produce are noisy and unstable. In these profiles, biomarkers are detected as signal regions (peaks), where control and disease samples behave differently. Mass spectrometry (MS) data generally contain a limited number of samples described by a high number of features. In this work, we present a novel class of evolutionary algorithms, estimation of distribution algorithms (EDA), as an efficient peak selector in this MS domain. There is a trade-of f between the reliability of the detected biomarkers and the low number of samples for analysis. For this reason, we introduce a consensus approach, built upon the classical EDA scheme, that improves stability and robustness of the final set of relevant peaks. An entire data workflow is designed to yield unbiased results. Four publicly available MS data sets (two MALDI-TOF and another two SELDI-TOF) are analyzed. The results are compared to the original works, and a new plot (peak frequential plot) for graphically inspecting the relevant peaks is introduced. A complete online supplementary page, which can be found at http://www.sc.ehu.es/ccwbayes/members/ruben/ms, includes extended info and results, in addition to Matlab scripts and references.

Cited By

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  • (2019)Solving system-level synthesis problem by a multi-objective estimation of distribution algorithmExpert Systems with Applications: An International Journal10.1016/j.eswa.2013.09.04941:5(2496-2513)Online publication date: 25-Nov-2019
  • (2019)A latent space-based estimation of distribution algorithm for large-scale global optimizationSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-018-3390-823:13(4593-4615)Online publication date: 17-Jul-2019
  • (2013)Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry dataInformation Sciences: an International Journal10.1016/j.ins.2010.12.013222(229-246)Online publication date: 1-Feb-2013
  • Show More Cited By

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Published In

cover image IEEE/ACM Transactions on Computational Biology and Bioinformatics
IEEE/ACM Transactions on Computational Biology and Bioinformatics  Volume 8, Issue 3
May 2011
288 pages

Publisher

IEEE Computer Society Press

Washington, DC, United States

Publication History

Published: 01 May 2011
Published in TCBB Volume 8, Issue 3

Author Tags

  1. EDA
  2. Mass spectrometry
  3. biomarker discovery.
  4. feature selection

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Cited By

View all
  • (2019)Solving system-level synthesis problem by a multi-objective estimation of distribution algorithmExpert Systems with Applications: An International Journal10.1016/j.eswa.2013.09.04941:5(2496-2513)Online publication date: 25-Nov-2019
  • (2019)A latent space-based estimation of distribution algorithm for large-scale global optimizationSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-018-3390-823:13(4593-4615)Online publication date: 17-Jul-2019
  • (2013)Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry dataInformation Sciences: an International Journal10.1016/j.ins.2010.12.013222(229-246)Online publication date: 1-Feb-2013
  • (2013)Regularized continuous estimation of distribution algorithmsApplied Soft Computing10.1016/j.asoc.2012.11.04913:5(2412-2432)Online publication date: 1-May-2013

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