Signal processing for molecular and cellular biological physics:an emerging field


Recent advances in our ability to watch the molecular and cellular processes of life in action-such as atomic force microscopy, optical tweezers and Forster fluorescence resonance energy transfer-raise challenges for digital signal processing (DSP) of the resulting experimental data. This article explores the unique properties of such biophysical time series that set them apart from other signals, such as the prevalence of abrupt jumps and steps, multi-modal distributions and autocorrelated noise. It exposes the problems with classical linear DSP algorithms applied to this kind of data, and describes new nonlinear and non-Gaussian algorithms that are able to extract information that is of direct relevance to biological physicists. It is argued that these new methods applied in this context typify the nascent field of biophysical DSP. Practical experimental examples are supplied.

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Divisions: College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
Additional Information: © 2012 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License, which permits unrestricted use, provided the original author and source are credited.
Uncontrolled Keywords: biophysics,molecules,cells,ital signal processing,Mathematics(all),Physics and Astronomy(all),Engineering(all)
Publication ISSN: 1471-2962
Last Modified: 17 May 2024 07:09
Date Deposited: 28 Jan 2013 16:06
Full Text Link: http://rsta.roy ... 1/1984/20110546
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2013-02-13
Published Online Date: 2012-12-31
Authors: Little, Max A (ORCID Profile 0000-0002-1507-3822)
Jones, Nick S.



Version: Published Version

License: Creative Commons Attribution

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