Cell Biochemistry Martinsried
the multimolecular cytometric analysis of the cellular heterogeneity of cytomes (cellular systems/organs/body) in combination with exhaustive bioinformatic knowledge extraction, access a maximum of information on the apparent molecular cell phenotype as it results from cell genotype and exposure.
Molecular cell phenotypes in the naturally existing cellular and cell population heterogeneity of disease affected body cytomes contain the information on the future development (prediction) as well as on the present status (diagnosis) of a disease.
Data classifications are presently considered predictive for individual patients at predictive values >95% for each classified disease category of the learning set while they are prognostic at values <95%. The effort will be to elevate this level to >99% through the search for more efficiently discriminating molecular data patterns.
for predictive medicine by cytomics:
a.) multiparametric cytometric determination of cell constituents or functions in disease associated cytomes
b.) analysis (1, 2) of all measured numeric parameters for all cell populations that is in practice for >95% of the collected cells
c.) data pattern classification of this entire information against patient's future disease course during the learning phase by exhaustive knowledge extraction
d.) classification of the embedded test set of patient data, measured under the same conditions as the learning set but remaining unknown to the learning process. Typically, every 5th or 10th patient is assigned to the test set prior to the learning phase to exclude classification biases.
e.) prospective classification of data collected from subsequent new patients during the clinical evaluation phase
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