Literature DB >> 18312217

Organizing a competition on clinical mass spectrometry based proteomic diagnosis.

Bart Mertens1.   

Abstract

This paper gives a description of the structure of the classification competition on mass spectrometry proteomic data which is presented in this issue. All steps according to which the competition was run, leading up to the joint meeting, are explained. The paper gives further details on the data analyzed by all participants. This includes information on the preprocessing steps carried out, with references to appropriate sources describing algorithms used, dimensionalities, definition of calibration and validation sets, sample and group sizes and a description of which data and information was made available to participants. The paper starts with a review of mass spectrometry proteomics from a statistical and bioinformatic viewpoint. We conclude with a discussion on the nature of the competition and some of the decisions made in implementing it.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18312217     DOI: 10.2202/1544-6115.1353

Source DB:  PubMed          Journal:  Stat Appl Genet Mol Biol        ISSN: 1544-6115


  3 in total

Review 1.  Image analysis tools and emerging algorithms for expression proteomics.

Authors:  Andrew W Dowsey; Jane A English; Frederique Lisacek; Jeffrey S Morris; Guang-Zhong Yang; Michael J Dunn
Journal:  Proteomics       Date:  2010-12       Impact factor: 3.984

2.  Combination approaches improve predictive performance of diagnostic rules for mass-spectrometry proteomic data.

Authors:  Alexia Kakourou; Werner Vach; Bart Mertens
Journal:  J Comput Biol       Date:  2014-12       Impact factor: 1.479

3.  A comparison of methods for classifying clinical samples based on proteomics data: a case study for statistical and machine learning approaches.

Authors:  Dayle L Sampson; Tony J Parker; Zee Upton; Cameron P Hurst
Journal:  PLoS One       Date:  2011-09-28       Impact factor: 3.240

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.