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Bioinformatics Proteome informatics

Wojcik, J. and Hamburger, A. (2003) Proteomic Informatics. In Bioinformatics for Geneticists. [Pg.184]

Fig. 4. Application of bioinformatics tools to 2D-DIGE data analysis. Proteome data consisting of the normalized spot intensity values are exported from the image analysis software and their correlation with clinicopathological data examined. Using informatics tools including clustering algorithms and machine-learning methods, a novel cancer classification based on proteome data is established, and key proteomic features and proteins corresponding to biomarker candidates are identified. Fig. 4. Application of bioinformatics tools to 2D-DIGE data analysis. Proteome data consisting of the normalized spot intensity values are exported from the image analysis software and their correlation with clinicopathological data examined. Using informatics tools including clustering algorithms and machine-learning methods, a novel cancer classification based on proteome data is established, and key proteomic features and proteins corresponding to biomarker candidates are identified.

See other pages where Bioinformatics Proteome informatics is mentioned: [Pg.53]    [Pg.100]    [Pg.124]    [Pg.238]    [Pg.740]    [Pg.19]    [Pg.4]    [Pg.9]    [Pg.515]    [Pg.754]   


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