The Application of Dynamic Time Warping to the Quality Evaluation of Radix Puerariae thomsonii: Correcting Retention Time Shift in the Chromatographic Fingerprints

Jiao, Long; Bing, Shan; Wang, Li; Li, Hua

doi:10.1093/chromsci/bmu161

Cited by 4 publications

(5 citation statements)

References 25 publications

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“…The PCA analysis was performed using a two-component model with a total variance 75.5% (PC1 44.9%, PC2 30.6%) for raw data and 85.4% (PC1 71.4%, PC2 14.0%) for adjusted data explained. With adequate results, the effect of retention time adjustment was also visualized in PCA in a previous study [60].…”

Section: The Efficacy Of Hplc Data Alignment Optimizationmentioning

confidence: 94%

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The Potential Use of Herbal Fingerprints by Means of HPLC and TLC for Characterization and Identification of Herbal Extracts and the Distinction of Latvian Native Medicinal Plants

et al. 2022

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The growing market of herbal medicines, the increase in international trade in Latvia, and the lack of adequate analytical methods have raised the question of the potential use of herbal fingerprinting methods. In this study, high-performance liquid chromatography (HPLC) and thin layer chromatography (TLC) methods were developed for obtaining chromatographic fingerprints of four taxonomically and evolutionary different medicinal plants (Hibiscus sabdariffa L., Calendula officinalis L., Matricaria recutita L., Achillea millefolium L.). Retention time shifting, principal component analysis (PCA), hierarchical cluster analysis (HCA), and orthogonal projections to latent structures (OPLS) analysis were used to improve and analyze the obtained fingerprints. HPLC data detection at 270 nm was determined superior to 360 nm for the distinction of medicinal plants and used data alignment method significantly increased similarity between samples. Analyzed medicinal plant extracts formed separate, compact clusters in PCA, and the results of HCA correlated with the evolutionary relationships of the analyzed medicinal plants. Herbal fingerprinting using chromatographic analysis coupled with multivariate analysis has a great potential for the identification of medicinal plants as well as for the distinction of Latvian native medicinal plants.

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Section: The Efficacy Of Hplc Data Alignment Optimizationmentioning

confidence: 94%

“…Raw Matricaria recutita L. samples were visually diverse and had the largest sample size, thereby possibly explaining the diversity of chemical composition between samples. In a study by Jiao et al, retention time alignment was applied to fingerprint analysis and also provided satisfactory results [60].…”

Section: The Efficacy Of Hplc Data Alignment Optimizationmentioning

confidence: 99%

The Potential Use of Herbal Fingerprints by Means of HPLC and TLC for Characterization and Identification of Herbal Extracts and the Distinction of Latvian Native Medicinal Plants

et al. 2022

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“…First, it is employed in speech recognition to compensate non-linear time shifts between two speech patterns as a consequence of different pronunciation [53][54][55]. Most recently, dynamic time warping is mainly used in the field of chemistry [56,57], gesture recognition [58,59], finance [34,60,61], and medicine [62,63].…”

Section: Dynamic Time Warpingmentioning

confidence: 99%

Epidemiology of Coronavirus COVID-19: Forecasting the Future Incidence in Different Countries

Stübinger

Schneider

2020

Healthcare

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This paper forecasts the future spread of COVID-19 by exploiting the identified lead-lag effects between different countries. Specifically, we first determine the past relation among nations with the aid of dynamic time warping. This procedure allows an elastic adjustment of the time axis to find similar but phase-shifted sequences. Afterwards, the established framework utilizes information about the leading country to predict the Coronavirus spread of the following nation. The presented methodology is applied to confirmed Coronavirus cases from 1 January 2020 to 28 March 2020. Our results show that China leads all other countries in the range of 29 days for South Korea and 44 days for the United States. Finally, we predict a future collapse of the healthcare systems of the United Kingdom and Switzerland in case of our explosion scenario.

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“…Originally, it is used within the framework of spoken word recognition, i.e., the technique eliminates non-linear time shifts between two speech patterns caused by different speaking rates (Juang, 1984;Rath and Manmatha, 2003;Muda et al, 2010). In recent times, dynamic time warping is especially utilized in gesture recognition (Arici et al, 2014;Cheng et al, 2016), chemistry (Jiao et al, 2014;Dupas et al, 2015), and medicine (Rakthanmanon et al, 2012;Fu et al, 2017). Surprisingly, there exist only two academic studies in the context of statistical arbitrage trading.…”

Section: Introductionmentioning

confidence: 99%

Statistical arbitrage with optimal causal paths on high-frequency data of the S&P 500

Stübinger

2018

Quantitative Finance

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This paper develops the optimal causal path algorithm and applies it within a fully-fledged statistical arbitrage framework to minute-by-minute data of the S&P 500 constituents from 1998 to 2015. Specifically, the algorithm efficiently determines the optimal non-linear mapping and the corresponding lead-lag structure between two time series. Afterwards, this study explores the use of optimal causal paths as a means for identifying promising stock pairs and for generating buy and sell signals. For this purpose, the established trading strategy exploits information about the leading stock to predict future returns of the following stock. The value-add of the proposed framework is assessed by benchmarking it with variants relying on classic similarity measures and a buy-and-hold investment in the S&P 500 index. In the empirical back-testing study, the trading algorithm generates statistically and economically significant returns of 54.98 percent p.a. and an annualized Sharpe ratio of 3.57 after transaction costs. Returns are well superior to the benchmark approaches and do not load on any common sources of systematic risk. The strategy outperforms in the context of cryptocurrencies even in recent times due to the fact that stock returns contain substantial information about the future bitcoin returns.

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The Application of Dynamic Time Warping to the Quality Evaluation of Radix Puerariae thomsonii: Correcting Retention Time Shift in the Chromatographic Fingerprints

Cited by 4 publications

References 25 publications

The Potential Use of Herbal Fingerprints by Means of HPLC and TLC for Characterization and Identification of Herbal Extracts and the Distinction of Latvian Native Medicinal Plants

The Potential Use of Herbal Fingerprints by Means of HPLC and TLC for Characterization and Identification of Herbal Extracts and the Distinction of Latvian Native Medicinal Plants

Epidemiology of Coronavirus COVID-19: Forecasting the Future Incidence in Different Countries

Statistical arbitrage with optimal causal paths on high-frequency data of the S&P 500

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