Group-Wise Principal Component Analysis for Exploratory Data Analysis

Catecholamines are physiological regulators of carbohydrate and lipid metabolism during stress, but their chronic influence on metabolic changes in obese patients is still not clarified. The present study aimed to establish the associations between the catecholamine metabolites and metabolic syndrome (MS) components in obese women as well as to reveal the possible hidden subgroups of patients through hierarchical cluster analysis and principal component analysis. The 24-h urine excretion of metanephrine and normetanephrine was investigated in 150 obese women (54 non diabetic without MS, 70 non-diabetic with MS and 26 with type 2 diabetes). The interrelations between carbohydrate disturbances, metabolic syndrome components and stress response hormones were studied. Exploratory data analysis was used to determine different patterns of similarities among the patients. Normetanephrine concentrations were significantly increased in postmenopausal patients and in women with morbid obesity, type 2 diabetes, and hypertension but not with prediabetes. Both metanephrine and normetanephrine levels were positively associated with glucose concentrations one hour after glucose load irrespectively of the insulin levels. The exploratory data analysis showed different risk subgroups among the investigated obese women. The development of predictive tools that include not only traditional metabolic risk factors, but also markers of stress response systems might help for specific risk estimation in obesity patients.

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Reaction Monitoring in Explorative Organic Synthesis Using Fiber-Optical NIR Spectroscopy and Principal Component Analysis

Applied Spectroscopy ◽

10.1366/0003702963904485 ◽

1996 ◽

Vol 50 (12) ◽

pp. 1541-1544 ◽

Cited By ~ 9

Author(s):

Hans-René Bjørsvik

Keyword(s):

Principal Component Analysis ◽

Data Analysis ◽

Latent Variables ◽

Near Infrared ◽

Nir Spectroscopy ◽

Principal Component ◽

Component Analysis ◽

Quantitative Information ◽

Chemistry Laboratory ◽

Reaction Profile

A method of combining spectroscopy and multivariate data analysis for obtaining quantitative information on how a reaction proceeds is presented. The method is an approach for the explorative synthetic organic laboratory rather than the analytical chemistry laboratory. The method implements near-infrared spectroscopy with an optical fiber transreflectance probe as instrumentation. The data analysis consists of decomposition of the spectral data, which are recorded during the course of a reaction by using principal component analysis to obtain latent variables, scores, and loading. From the scores and the corresponding reaction time, it is possible to obtain a reaction profile. This reaction profile can easily be recalculated to obtain the concentration profile over time. This calculation is based on only two quantitative measurements, which can be (1) measurement from the work-up of the reaction or (2) chromatographic analysis from two withdrawn samples during the reaction. The method is applied to the synthesis of 3-amino-propan-1,2-diol.

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On the utilization of principal component analysis in laser-induced breakdown spectroscopy data analysis, a review

Spectrochimica Acta Part B Atomic Spectroscopy ◽

10.1016/j.sab.2018.05.030 ◽

2018 ◽

Vol 148 ◽

pp. 65-82 ◽

Cited By ~ 49

Author(s):

Pavel Pořízka ◽

Jakub Klus ◽

Erik Képeš ◽

David Prochazka ◽

David W. Hahn ◽

...

Keyword(s):

Principal Component Analysis ◽

Data Analysis ◽

Principal Component ◽

Component Analysis ◽

Laser Induced Breakdown Spectroscopy ◽

Spectroscopy Data ◽

Breakdown Spectroscopy ◽

Laser Induced Breakdown

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Statistical approaches in literature: An application of principal component analysis and factor analysis to analyze the different arrangements about the Quran’s Suras

Digital Scholarship in the Humanities ◽

10.1093/llc/fqaa006 ◽

2020 ◽

Author(s):

Yanwen Wang ◽

Javad Garjami ◽

Milena Tsvetkova ◽

Nguyen Huu Hau ◽

Kim-Hung Pho

Keyword(s):

Data Mining ◽

Principal Component Analysis ◽

Factor Analysis ◽

Data Analysis ◽

Principal Component ◽

Component Analysis ◽

Holy Quran ◽

The Holy Quran ◽

Statistical Approaches

Abstract Data mining, statistics, and data analysis are popular techniques to study datasets and extract knowledge from them. In this article, principal component analysis and factor analysis were applied to cluster thirteen different given arrangements about the Suras of the Holy Quran. The results showed that these thirteen arrangements can be categorized in two parts such that the first part includes Blachère, Davood, Grimm, Nöldeke, Bazargan, E’temad-al-Saltane and Muir, and the second part includes Ebn Nadim, Jaber, Ebn Abbas, Hazrat Ali, Khazan, and Al-Azhar.

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Entwicklung, Beobachtung und Steuerung integrierter, quasi-kontinuierlicher pharmazeutischer Produktionsprozesse mit Methoden der Multivariaten Datenverarbeitung

10.51202/9783186292179 ◽

2016 ◽

Author(s):

Sven-Oliver Borchert

Keyword(s):

Principal Component Analysis ◽

Data Analysis ◽

Multivariate Data Analysis ◽

Process Analytical Technology ◽

Multivariate Data ◽

Principal Component ◽

Component Analysis ◽

Analytical Technology

Die vorliegende Arbeit befasst sich mit Aspekten einer modernen Bioverfahrenstechnik am Beispiel von Prozessen zur Herstellung rekombinanter potentieller Malariavakzine. Dabei wurden zwei quasi-kontinuierliche Prozesse aus herkömmlichen Batch-Unit Operationen aufgebaut, in denen die Anwendung von Process Analytical Technology im Vordergrund steht. Das Hauptaugenmerk dieser Arbeit lag dabei auf einer Implementierung der Multivariate Data Analysis zum Monitoring und zur Evaluierung des zyklischen Prozessablaufes und seiner Reproduzierbarkeit. Im Bereich der Principal Component Analysis wurde die Methode der Prozessüberwachung mit dem Golden Batch-Tunnel angewendet. Mit dem Golden Batch-Ansatz wurden Methoden zur Prozessprädiktion implementiert und mit einer Model Predictive Multivariate Control auch zur Steuerung von realen Prozesses erprobt. Darüber hinaus wurde die MVDA zur Prädiktion von Medienkomponenten sowie deren zellspezifische Reaktionsraten aus klassischen Onli...

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