Abstract

An ion-channel platform can be used for stochastic sensing at the molecule level. Digital signal processing techniques can be applied for detection, classification, and de-noising of ion-channel signals. In this paper, we present feature extraction and classification techniques for the analysis of the stochastic response of porin OmpF and α-hemolysin to several different analytes. In particular, we examine unitary transform representations of ionchannel currents. We study two transforms, namely, the Fourier transform and the Walsh transform. Preliminary results using a Hidden Markov model classifier are presented.

Original languageEnglish (US)
Title of host publicationProceedings of the 5th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, SPPRA 2008
Pages272-275
Number of pages4
StatePublished - Dec 1 2008
Event5th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, SPPRA 2008 - Innsbruck, Austria
Duration: Feb 13 2008Feb 15 2008

Publication series

NameProceedings of the 5th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, SPPRA 2008

Other

Other5th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, SPPRA 2008
CountryAustria
CityInnsbruck
Period2/13/082/15/08

Keywords

  • DSP
  • Feature extraction and classification
  • Ion-channel sensors
  • Walsh transform

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing

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