We've updated our Privacy Policy to make it clearer how we use your personal data.

We use cookies to provide you with a better experience. You can read our Cookie Policy here.

Advertisement

Effective Fishing of Characteristic Proteome Fractions and Identification of Biomarkers Therein: Application of VisualCockpit to Multidimensional Chromatogram and MS Data

Introduction
Two different strategies may be used for fishing biomarkers via proteomics based methods :

1) All proteome fractions – eventually some thousands – generated from different samples are analyzed, quantified, and compared. This causes high operating effort and requires high throughput methods for analysis and data handling which are not available with all analytical procedures. This strategy provides the possibility to find all biomarker candidates detectable, however, their number is confined by the analytical methods at hand and the possible operating effort.

2) Otherwise, start with pre-selection of characteristic fractions and focus the operating expense on careful and comprehensive analysis of these fractions using an adequate assortment of different analytical strategies. With this strategy biomarker yield depends on the pre-selection criteria.
Depending on the separation procedure, characteristic fractions may be identified by double staining with 2DE, characteristic tags, other task-specific properties or simply by protein quantification.

Here we introduce an efficient pre-selection based on optical properties of the fractions. Logical selection criteria are applied to sequentially reduce the fractions that have to be analyzed further. Appropriate subsets of fractions are produced and visualized by the software package VisualCockpit. This software can be applied in principle to all data formats and to both fishing strategies, and to evaluation of separation procedures.

Advertisement