ClinProTools uses a range of algorithms for generating classification models. Genetic Algorithm which mimics evolution in nature, Support Vector Machine motivated from statistical learning theory, Supervised Neural Network (SNN) and QuickClassifier, an univariate sorting algorithm using the p-values at certain peak positions for classification are included.

Established statistical approaches such as T-Test, ANOVA-Test, Unsupervised Clustering, Principle Component Analysis (PCA) or outlier detection by pattern matching are used for statistical testing of the data sets.

Powerful intuitive visualization such as virtual gel view and stack view of data from larger sample cohorts is the strength of ClinProTools.

ClinProTools offers various types of result reports to report specific spectra, peak statistic, model, validation or classification data as well as error information.
Correlation Matrix reports are as well available as Model or Validation reports.

For increasing the possibilities of biomarker identification and characterization and to complement the Bruker Daltonics biomarker discovery platform a direct link to flexImaging™ software provides comprehensive visualization of the spatial distribution of biomarker candidates in a tissue.

The integration of easy-to-use ClinProTools and flexImaging bioinformatics solutions creates a powerful combination for peak profile classification and MALDI imaging in investigating the distributions of peptides and proteins in tissue samples, known as Class Imaging™ (Patent pending). It allows the classification of tissue types, such as carcinoma, and determination of the class membership of comparable tissues/biopsies.