A novel method for analysis of single ion channel signal based on wavelet transform

Chen, Z. Y.; Guo, Xingpeng; Zhang, X. L.; Cram, W. J.; Li, Z. W.

doi:10.1016/j.compbiomed.2006.08.006

Cited by 7 publications

(8 citation statements)

References 9 publications

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“…The PSD of the ion-channel signals exhibits low-pass characteristics and the corner frequency represents the average opening time of the channel [10]. This shows that the Fourier power spectrum contains sufficient discriminatory information to distinguish between different ion-channel signals.…”

Section: Power Spectramentioning

confidence: 96%

Analyte detection using an ion-channel sensor array

Sattigeri

Ramamurthy

Thiagarajan

et al. 2011

2011 17th International Conference on Digital Signal Processing (DSP)

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Ion-channel sensors can be used for detecting small metal ions and organic molecules. The sensor consists of a chamber with a lipid bilayer hosting ion channels produced by protein insertion. These channels allow selective transport and produce a characteristic signal across the chamber for each analyte. A four chamber ion channel sensor array is built for accurate analyte detection. In this paper, we address the case in which non-uniform number of channels formed in each chamber. The power distribution information in the transform domain is used as features for each chamber signal. We employ support vector regression to estimate the number of channels inserted in each chamber and normalize the chamber signal features. The change observed in the normalized features of the chamber containing the analyte with respect to other chambers is used for detection. Results show high accuracy rates for detection of analyte using simulated data and experimental data.

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Section: Power Spectramentioning

confidence: 96%

Analyte detection using an ion-channel sensor array

Sattigeri

Ramamurthy

Thiagarajan

et al. 2011

2011 17th International Conference on Digital Signal Processing (DSP)

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“…In Section 4.1, we showed that the PSD is dependent only on the eigen decomposition of the state transition matrix and it will always exhibit low-pass characteristics. Furthermore, if we denote f s as the sampling frequency and f c as the frequency where the flat and sloping portions of the PSD intersect, 1/f c represents the average opening time of the channel [13]. This shows that the Fourier power spectrum contains sufficient discriminatory information to distinguish between different ion-channel signals.…”

Section: Fourier Domain Featuresmentioning

confidence: 98%

“…The scalogram defined in (9) is used as the wavelet domain feature and it is just a scaled version of the PDF described in [13]. We use the Haar wavelet, as it has a shape that correlates well with the general switching state structure of an ion-channel signal.…”

Section: Wavelet Domain Featuresmentioning

confidence: 99%

“…The stationarity of the ion-channel signals and the changes in the kinetics of ion-channels have been analyzed using the wavelet transform [12]. Chen et al have used the power distribution fraction (PDF) in the wavelet domain and the power spectral density (PSD) in the Fourier domain to infer the average opening time of the ion-channel [13].…”

Section: Introductionmentioning

confidence: 99%

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Transform domain features for ion-channel signal classification

Ramamurthy

Thiagarajan

Sattigeri

et al. 2011

Biomedical Signal Processing and Control

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“…The PSD of an ion-channel signals exhibits low-pass characteristics and the corner frequency represents the average opening time of the channel [9]. The PSD is estimated using the Welch procedure given in [10].…”

Section: A Power Spectral Density As Discriminatory Featuresmentioning

confidence: 99%

Robust PSD features for ion-channel signals

Sattigeri¹,

Thiagarajan²,

Ramamurthy³

et al. 2011

Sensor Signal Processing for Defence (SSPD 2011)

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Ion-channel sensors which mimic naturally occurring pore-forming proteins can be used to detect small metal ions and organic molecules. A chamber with a lipid bilayer hosting ion-channels produced by protein insertion constitutes such a sensor. Each analyte produces a characteristic signal pattern during its migration from one section of the chamber to another through the ion-channels. A four chamber ion-channel sensor array is built for accurate analyte detection. The power distribution information in the transform domain has been successfully used as discriminatory features for each chamber signal. However, these features are not robust to noise and hence result in a reduced classification performance. In this paper, we pose the stabilization of PSD features extracted from noisy segments as a matrix completion problem. Matrix completion with a low rank assumption provides the stabilized features. We demonstrate using a synthetic experiment that the proposed setup achieves improved classification performance in comparison to using the features directly. Furthermore, performing analyte detection in real ion-channel data, using the proposed robust features, provides reduction in false alarm rates.

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A novel method for analysis of single ion channel signal based on wavelet transform

Cited by 7 publications

References 9 publications

Analyte detection using an ion-channel sensor array

Analyte detection using an ion-channel sensor array

Transform domain features for ion-channel signal classification

Robust PSD features for ion-channel signals

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