Paper
26 June 1992 Maximum-likelihood estimation of restriction-fragment mobilities from 1-D electrophoretic agarose gels
Heather A. Drury, David G. Politte, John M. Ollinger, Philip Green, Lewis J. Thomas Jr.
Author Affiliations +
Proceedings Volume 1660, Biomedical Image Processing and Three-Dimensional Microscopy; (1992) https://doi.org/10.1117/12.59585
Event: SPIE/IS&T 1992 Symposium on Electronic Imaging: Science and Technology, 1992, San Jose, CA, United States
Abstract
We have developed a technique for finding maximum-likelihood estimates of DNA restriction- fragment mobilities from images of fluorescently stained electrophoretic gels. Gel images are acquired directly using a CCD camera. The likelihood model incorporates the Poisson nature of the photon counts and models the fluorescence intensity as the superposition of Gaussian functions (corresponding to the fragment bands) of varying magnitude and width. An expectation-maximization algorithm is used to find maximum-likelihood estimates of the number of fragments, fragment mobilities, widths of the bands, background contributions, and DNA concentration. This approach has several advantages. Closely spaced and overlapping fragments are accurately resolved into their components. No a priori knowledge of the number or positions of fragments is required. Fragment lengths estimated by the maximum-likelihood method from experimental data were compared to the known lengths of fragments generated from three different restriction digests of bacteriophage (lambda) DNA. Preliminary results using the maximum-likelihood method indicate residual sizing errors on the order of 1%.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Heather A. Drury, David G. Politte, John M. Ollinger, Philip Green, and Lewis J. Thomas Jr. "Maximum-likelihood estimation of restriction-fragment mobilities from 1-D electrophoretic agarose gels", Proc. SPIE 1660, Biomedical Image Processing and Three-Dimensional Microscopy, (26 June 1992); https://doi.org/10.1117/12.59585
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KEYWORDS
Expectation maximization algorithms

Image processing

Biomedical optics

3D image processing

Microscopy

CCD cameras

Signal processing

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