Regression Algorithm for Identification of Biomarker Areas in SELDI-TOF Mass Spectra
| Authors | |
|---|---|
| Year of publication | 2014 |
| Type | Article in Periodical |
| Magazine / Source | International Journal of Imaging and Robotics |
| MU Faculty or unit | |
| 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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