Abstract
One of the critical steps in two-dimensional electrophoresis (2-DE) image pre-processing is the denoising, that might aggressively affect either spot detection or pixel-based methods. The Median Modified Wiener Filter (MMWF), a new nonlinear adaptive spatial filter, resulted to be a good denoising approach to use in practice with 2-DE. MMWF is suitable for global denoising, and contemporary for the removal of spikes and Gaussian noise, being its best setting invariant on the type of noise. The second critical step rises because of the fact that 2-DE gel images may contain high levels of background, generated by the laboratory experimental procedures, that must be subtracted for accurate measurements of the proteomic optical density signals. Here we discuss an efficient mathematical method for background estimation, that is suitable to work even before the 2-DE image spot detection, and it is based on the 3D mathematical morphology (3DMM) theory.
Both authors have equally contributed.
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Acknowledgements
M.A. is supported by AIRC Special Program Molecular Clinical Oncology 5 per mille n.9965. C.V.C. is supported by the independent group leader starting grant of the Technische Universität Dresden (TUD).
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Cannistraci, C.V., Alessio, M. (2016). Image Pretreatment Tools I: Algorithms for Map Denoising and Background Subtraction Methods. In: Marengo, E., Robotti, E. (eds) 2-D PAGE Map Analysis. Methods in Molecular Biology, vol 1384. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3255-9_5
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DOI: https://doi.org/10.1007/978-1-4939-3255-9_5
Publisher Name: Humana Press, New York, NY
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