Chemometric variance analysis of 1H NMR metabolomics data on the effects of oral rinse on saliva

[1]  R. A. van den Berg,et al.  Simultaneous analysis of coupled data matrices subject to different amounts of noise. , 2011, The British journal of mathematical and statistical psychology.

[2]  Julie E. Zeskind,et al.  Mouse urinary biomarkers provide signatures of maturation, diet, stress level, and diurnal rhythm. , 2010, Chemical senses.

[3]  R. Brereton,et al.  Self-organizing map quality control index. , 2010, Analytical Chemistry.

[4]  R. Brereton,et al.  Support vector machines for classification and regression. , 2010, The Analyst.

[5]  R. Brereton,et al.  Supervised self organizing maps for classification and determination of potentially discriminatory variables: illustrated by application to nuclear magnetic resonance metabolomic profiling. , 2010, Analytical chemistry.

[6]  Age K. Smilde,et al.  Multivariate paired data analysis: multilevel PLSDA versus OPLSDA , 2009, Metabolomics.

[7]  Martin Grootveld,et al.  Self Organising Maps for variable selection: Application to human saliva analysed by nuclear magnetic resonance spectroscopy to investigate the effect of an oral healthcare product , 2009 .

[8]  Richard G. Brereton,et al.  Chemometrics for Pattern Recognition , 2009 .

[9]  Age K. Smilde,et al.  Exploring the analysis of structured metabolomics data , 2009 .

[10]  Iven Van Mechelen,et al.  UvA-DARE ( Digital Academic Repository ) A structured overview of simultaneous component based data integration , 2009 .

[11]  Sila Kittiwachana,et al.  Multilevel simultaneous component analysis for fault detection in multicampaign process monitoring: application to on-line high performance liquid chromatography of a continuous process. , 2009, The Analyst.

[12]  Maria E. Holmboe,et al.  Monte-Carlo methods for determining optimal number of significant variables. Application to mouse urinary profiles , 2009, Metabolomics.

[13]  Tormod Næs,et al.  Interpreting sensory data by combining principal component analysis and analysis of variance , 2009 .

[14]  R. Brereton,et al.  Comparison of performance of five common classifiers represented as boundary methods: Euclidean Distance to Centroids, Linear Discriminant Analysis, Quadratic Discriminant Analysis, Learning Vector Quantization and Support Vector Machines, as dependent on data structure , 2009 .

[15]  Heng Tao Shen,et al.  Principal Component Analysis , 2009, Encyclopedia of Biometrics.

[16]  Age K Smilde,et al.  Multilevel data analysis of a crossover designed human nutritional intervention study. , 2008, Journal of proteome research.

[17]  Andreas Christmann,et al.  Support vector machines , 2008, Data Mining and Knowledge Discovery Handbook.

[18]  Age K. Smilde,et al.  The geometry of ASCA , 2008 .

[19]  E. Vaughan,et al.  1H NMR metabolite profiling of feces as a tool to assess the impact of nutrition on the human microbiome , 2008, NMR in biomedicine.

[20]  Rasmus Bro,et al.  PARAFASCA: ASCA combined with PARAFAC for the analysis of metabolic fingerprinting data , 2008 .

[21]  Age K. Smilde,et al.  UvA-DARE ( Digital Academic Repository ) Assessment of PLSDA cross validation , 2008 .

[22]  Hiroshi Mori,et al.  Comparative Metagenomics Revealed Commonly Enriched Gene Sets in Human Gut Microbiomes , 2007, DNA research : an international journal for rapid publication of reports on genes and genomes.

[23]  Age K. Smilde,et al.  Statistical validation of megavariate effects in ASCA , 2007, BMC Bioinformatics.

[24]  Age K. Smilde,et al.  Discovering gene expression patterns in time course microarray experiments by ANOVA-SCA , 2007, Bioinform..

[25]  D. Penn,et al.  A fuzzy distance metric for measuring the dissimilarity of planar chromatographic profiles with application to denaturing gradient gel electrophoresis data from human skin microbes: demonstration of an individual and gender-based fingerprint. , 2007, In Analysis.

[26]  D. Penn,et al.  Comparison of human axillary odour profiles obtained by gas chromatography/mass spectrometry and skin microbial profiles obtained by denaturing gradient gel electrophoresis using multivariate pattern recognition , 2007, Metabolomics.

[27]  Richard G. Brereton,et al.  Pattern Recognition of Gas Chromatography Mass Spectrometry of Human Volatiles in Sweat to distinguish the sex of subjects and determine potential Discriminatory Marker Peaks , 2007 .

[28]  A. Smilde,et al.  Assessing the statistical validity of proteomics based biomarkers. , 2007, Analytica chimica acta.

[29]  Richard G. Brereton,et al.  Applied Chemometrics for Scientists , 2007 .

[30]  R. Brereton.  Consequences of sample size, variable selection, and model validation and optimisation, for predicting classification ability from analytical data , 2006 .

[31]  Marieke E Timmerman,et al.  Multilevel component analysis. , 2006, The British journal of mathematical and statistical psychology.

[32]  J. J. Jansen,et al.  ASCA: analysis of multivariate data obtained from an experimental design , 2005 .

[33]  Peter de B. Harrington,et al.  Analysis of variance–principal component analysis: A soft tool for proteomic discovery , 2005 .

[34]  Age K. Smilde,et al.  ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data , 2005, Bioinform..

[35]  Onno E. de Noord,et al.  Multilevel component analysis and multilevel PLS of chemical process data , 2005 .

[36]  F. Bäckhed,et al.  Host-Bacterial Mutualism in the Human Intestine , 2005, Science.

[37]  Age K. Smilde,et al.  Multilevel component analysis of time-resolved metabolic fingerprinting data , 2005 .

[38]  David E. Booth,et al.  Chemometrics: Data Analysis for the Laboratory and Chemical Plant , 2004, Technometrics.

[39]  Jutta Joormann,et al.  Power and measures of effect size in analysis of variance with fixed versus random nested factors. , 2003, Psychological methods.

[40]  Bruce E. Ankenman,et al.  OPTIMAL DESIGNS FOR MIXED-EFFECTS MODELS WITH TWO RANDOM NESTED FACTORS , 2003 .

[41]  Marieke E. Timmerman,et al.  Four simultaneous component models for the analysis of multivariate time series from more than one subject to model intraindividual and interindividual differences , 2003 .

[42]  R. Bro,et al.  Centering and scaling in component analysis , 2003 .

[43]  M. Grootveld,et al.  1H and 13C NMR Spectroscopic Analysis of Human Saliva , 2002, Journal of dental research.

[44]  Jo Campling,et al.  Analysis of Variance (ANOVA) , 2002 .

[45]  J. Gordon,et al.  How host-microbial interactions shape the nutrient environment of the mammalian intestine. , 2002, Annual review of nutrition.

[46]  Johanna Smeyers-Verbeke,et al.  Handbook of Chemometrics and Qualimetrics: Part A , 1997 .

[47]  D. Beighton,et al.  Effect of use of 0.05% cetylpyridinium chloride mouthwash on normal oral flora. , 1997, Journal of dentistry.

[48]  Joop J. Hox,et al.  Applied Multilevel Analysis. , 1995 .

[49]  Henk A. L. Kiers,et al.  Hierarchical relations between methods for simultaneous component analysis and a technique for rotation to a simple simultaneous structure , 1994 .

[50]  Svante Wold,et al.  Analysis of variance (ANOVA) , 1989 .

[51]  Henk A. L. Kiers,et al.  Alternating least squares algorithms for simultaneous components analysis with equal component weight matrices in two or more populations , 1989 .

[52]  W. D. Miller.  THE MICROÖRGANISMS OF THE HUMAN MOUTH , 1891 .