Principles and applications of wavelet transformation to chemometrics

Jetter, Kurt; Depczynski, U.; Molt, Karl; Niemöller, A.

doi:10.1016/s0003-2670(00)00889-8

Cited by 95 publications

(42 citation statements)

References 21 publications

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“…The algorithm is based on the wavelet regression method, a computationally very efficient approach to data analysis. 22 Activity flag cutoffs were then based on both percentage effect from raw data and corrected data. The percentage effect for each compound was calculated as follows: %effect = 100 × [1 -(test compound -median min control)/(median Max control -median min control)].…”

Section: Hts Compound Library Screeningmentioning

confidence: 99%

Development of a High-Content High-Throughput Screening Assay for the Discovery of ATM Signaling Inhibitors

Bardelle

Boros

2012

SLAS Discovery

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The genome is constantly exposed to DNA damage agents, leading up to as many as 1 million individual lesions per cell per day. Cells have developed a variety of DNA damage repair (DDR) mechanisms to respond to harmful effects of DNA damage. Failure to repair the damaged DNA causes genomic instability and, as a result, leads to cellular transformation. Indeed, deficiencies of DDR frequently occur in human cancers, thus providing a great opportunity for cancer therapy by developing anticancer agents that work by synthetic lethality-based mechanisms or enhancing the clinical efficacy of radiotherapy and existing chemotherapies. Ataxia-telangiectasia mutated (ATM) plays a key role in regulating the cellular response to DNA double-strand breaks. Ionizing radiation causes double-strand breaks and induces rapid ATM autophosphorylation on serine 1981 that initiates ATM kinase activity. Activation of ATM results in phosphorylation of many downstream targets that modulate numerous damage-response pathways, most notably cell-cycle checkpoints. We describe here the development and validation of a high-throughput imaging assay measuring levels of phospho-ATM Ser1981 in HT29 cells after exposure to ionizing radiation. We also examined activation of downstream ATM effectors and checked specificity of the endpoint using known inhibitors of DNA repair pathways.

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Section: Hts Compound Library Screeningmentioning

confidence: 99%

Development of a High-Content High-Throughput Screening Assay for the Discovery of ATM Signaling Inhibitors

Bardelle

Boros

2012

SLAS Discovery

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“…Some popular preprocessing techniques, including a derivative method (Karstang and Kvalheim, 1991), Fourier filtering (Arnold and Small, 1990), and orthogonal signal correction (Svensson et al, 2002), have been used to remove background signals and noise from spectral data. Recently, wavelet transform methods have been widely used as alternative preprocessing tools in VIS/NIR spectral analysis (Walczak and Massart, 1997;Jetter et al, 2000). Studies have demonstrated that a discrete wavelet transform (DWT) is an excellent tool for fine-and coarse-scale spectral feature separation in hyperspectral data (Bruce and Koger, 2002;Zhang et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Applications of Discrete Wavelet Analysis for Predicting Internal Quality of Cherry Tomatoes using VIS/NIR Spectroscopy

Kim¹,

Kim²,

Kim³

et al. 2013

Journal of Biosystems Engineering

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Purpose: This study evaluated the feasibility of using a discrete wavelet transform (DWT) method as a preprocessing tool for visible/near-infrared spectroscopy (VIS/NIRS) with a spectroscopic transmittance dataset for predicting the internal quality of cherry tomatoes. Methods: VIS/NIRS was used to acquire transmittance spectrum data, to which a DWT was applied to generate new variables in the wavelet domain, which replaced the original spectral signal for subsequent partial least squares (PLS) regression analysis and prediction modeling. The DWT concept and its importance are described with emphasis on the properties that make the DWT a suitable transform for analyzing spectroscopic data. Results: The R 2 values and root mean squared errors (RMSEs) of calibration and prediction models for the firmness, sugar content, and titratable acidity of cherry tomatoes obtained by applying the DWT to a PLS regression with a set of spectra showed more enhanced results than those of each model obtained from raw data and mean normalization preprocessing through PLS regression. Conclusions:The developed DWT-incorporated PLS models using the db5 wavelet base and selected approximation coefficients indicate their feasibility as good preprocessing tools by improving the prediction of firmness and titratable acidity for cherry tomatoes with respect to R 2 values and RMSEs.

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“…13,14 Wavelet transform is a strong tool for signal de-noising 15 and baseline removal, 16 signal compression and processing, and multicomponent analysis; it has been established as a powerful technique in analytical chemistry. [17][18][19][20] By means of wavelet transform, an original signal can be decomposed into localized contributions characterized by a scale parameter. Each contribution represents a portion of the signal with a different frequency.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Spectrophotometric Determination of Metformin Hydrochloride and Glibenclamide in Binary Mixtures Using Combined Discrete and Continuous Wavelet Transforms

2011

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Principles and applications of wavelet transformation to chemometrics

Cited by 95 publications

References 21 publications

Development of a High-Content High-Throughput Screening Assay for the Discovery of ATM Signaling Inhibitors

Development of a High-Content High-Throughput Screening Assay for the Discovery of ATM Signaling Inhibitors

Applications of Discrete Wavelet Analysis for Predicting Internal Quality of Cherry Tomatoes using VIS/NIR Spectroscopy

Simultaneous Spectrophotometric Determination of Metformin Hydrochloride and Glibenclamide in Binary Mixtures Using Combined Discrete and Continuous Wavelet Transforms

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