Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06) (2006)
Hong Kong, China
Dec. 18, 2006 to Dec. 22, 2006
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDMW.2006.9
Frank Klawonn , University of Applied Sciences BS/WF, Germany
Claudia Hundertmark , Helmholtz Centre for Infection Research, Braunschweig, Germany
Lothar Jansch , Helmholtz Centre for Infection Research, Braunschweig, Germany
Often, measurement of biological components generates results, that are corrupted by noise. Noise can be caused by various factors like the detectors themselves, sample properties or also the process of data processing and appears independently from the applied technology. When measuring two identical samples it can be observed that similar signal intensities may have inherent but varying levels of noise and that the ratio of noise decreases with increasing signal intensities. In this paper a statistical approach is introduced to estimate the noise inherent in the measured data. Based on this estimation, it is possible to provide information about the reliability of a measured signal and whether the difference between intensities is mainly caused by noise or by biological relevant cellular alterations.
F. Klawonn, L. Jansch and C. Hundertmark, "A Maximum Likelihood Approach to Noise Estimation for Intensity Measurements in Biology," Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)(ICDMW), Hong Kong, China, 2006, pp. 180-184.