A Maximum Likelihood Approach to Noise Estimation for Intensity Measurements in Biology

Author

Klawonn, Frank ; Hundertmark, Claudia ; Jansch, Lothar

Author_Institution

Dept. of Comput. Sci., Appl. Sci. BS/WF Univ., Wolfenbuettel

fYear

2006

fDate

Dec. 2006

Firstpage

180

Lastpage

184

Abstract

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

Keywords

biomedical measurement; maximum likelihood estimation; medical signal processing; noise measurement; biological component measurement; biological relevant cellular alterations; data processing; intensity measurements; maximum likelihood approach; noise estimation; signal intensities; statistical approach; Bayesian methods; Biology; Circuit noise; Detectors; Maximum likelihood estimation; Noise generators; Noise level; Noise measurement; Proteins; Signal to noise ratio;

fLanguage

English

Publisher

ieee

Conference_Titel

Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on

Conference_Location

Hong Kong

Print_ISBN

0-7695-2702-7

Type

conf

DOI

10.1109/ICDMW.2006.9

Filename

4063621