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

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Authors	KNÍŽEK Jiří BOUCHAL Pavel VOJTĚŠEK Bořivoj NENUTIL Rudolf BERÁNEK Ladislav KUBA Martin TOMŠÍK Pavel
Year of publication	2014
Type	Article in Periodical
Magazine / Source	International Journal of Imaging and Robotics
MU Faculty or unit	Faculty of Science
Citation
Web	URL
Field	General mathematics
Keywords	Markers; molecular biology; mass spectra; gnostics; supercomputer.
Description	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.
Related projects:	Studium molekulárních mechanismů časného metastazování do lymfatických uzlin u karcinomu prsu nízkého stupně malignity pomocí proteomických technik