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Journal Article

Idealizing ion channel recordings by a jump segmentation multiresolution filter.

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Munk,  A.
Research Group of Statistical Inverse-Problems in Biophysics, MPI for biophysical chemistry, Max Planck Society;

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Citation

Hotz, T., Schuette, O. M., Sieling, H., Polupanow, T., Diederichsen, U., Steinem, C., et al. (2013). Idealizing ion channel recordings by a jump segmentation multiresolution filter. IEEE Transactions on Nanobioscience, 12(4), 376-386. doi:10.1109/TNB.2013.2284063.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0015-7EAF-C
Abstract
Based on a combination of jump segmentation and statistical multiresolution analysis for dependent data, a new approach called J-SMURF to idealize ion channel recordings has been developed. It is model-free in the sense that no a-priori assumptions about the channel's characteristics have to be made; it thus complements existing methods which assume a model for the channel's dynamics, like hidden Markov models. The method accounts for the effect of an analog filter being applied before the data analysis, which results in colored noise, by adapting existing muliresolution statistics to this situation. J-SMURF's ability to denoise the signal without missing events even when the signal-to-noise ratio is low is demonstrated on simulations as well as on ion current traces obtained from gramicidin A channels reconstituted into solvent-free planar membranes. When analyzing a newly synthesized acylated system of a fatty acid modified gramicidin channel, we are able to give statistical evidence for unknown gating characteristics such as subgating.