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

Max A Little, Nick S. Jones

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
Article number20110546
JournalPhilosophical Transactions A
Issue number1984
Early online date31 Dec 2012
Publication statusPublished - 13 Feb 2013

Bibliographical note

© 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.


  • biophysics
  • molecules
  • cells
  • ital signal processing


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