The use of engineered nanopores as sensing elements for chemical and biological agents is a rapidly developing area. The distinct signatures of nanopore-nanoparticle lend themselves to statistical analysis. As a result, processing of signals from these sensors is attracting a lot of attention. In this paper we demonstrate a neural network approach to classify and interpret nanopore and ion-channel signals.

Original languageEnglish (US)
Title of host publicationArtificial Neural Networks - ICANN 2009 - 19th International Conference, Proceedings
Number of pages10
EditionPART 2
StatePublished - 2009
Event19th International Conference on Artificial Neural Networks, ICANN 2009 - Limassol, Cyprus
Duration: Sep 14 2009Sep 17 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5769 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other19th International Conference on Artificial Neural Networks, ICANN 2009


  • Denoising using wavelets
  • Ion-channel sensors
  • Nanopore devices
  • PCA
  • Sensing using nanopores and neural networks
  • WHT

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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