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Regression Algorithm for Identification of Biomarker Areas in SELDI-TOF Mass Spectra

J. Knizek, P. Bouchal, B. Vojtesek, R. Nenutil, L. Beranek, M. Kuba, P. Tomsik

Abstract


We describe a special regression algorithm for the identification of biomarker areas in SELDI-TOF mass spectra in this paper. Tests in a set of orthogonal polynomial regressions is the basic principle of this approach. Gnostic cluster analysis is then a very effective algorithmic complement, especially, for a case of excessive behavior of a part of (bio)markers. Apart from this another a new way of TIC-normalization of data is proposed in this paper. This new regression algorithm averages results significantly more effectively than software systems used. A very considerable amount of computation was made on a supercomputer.

Keywords


Markers; Molecular biology; Mass spectra; Gnostics; Supercomputer.

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