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.
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