Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 7 of 7 for “"Sample classification"”.
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Statistical Analysis of Gene Expression Profile: Transcription Network Inference and Sample Classification
… gene expression patterns for classifying samples, to discover regulatory gene networks using natural genetic perturbations, to develop statistical methods for model fitting and comparison of biochemical networks, and eventually to advance our capability to understand the principles of …
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Analyzing geological materials under martian conditions using laser-induced breakdown spectroscopy : plasma fundamentals, sample classification, and trace element quanitification
… major, minor and trace elements on unprepared samples either in a laboratory setting or in situ. A significant advancement in LIBS research is the recent deployment of ChemCam to the surface of Mars at Gale crater onboard the Mars Science Laboratory (MSL) rover, Curiosity. ChemCam consists of a …
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Signal enhancement and data mining for biological and chemical samples using mass spectrometry
… of the complexity of chemical and biological samples, computer-assisted mass spectra analysis, including signal enhancement, statistics and machine learning, has been drawn more and more attention especially for researches in biomarker identification, sample classification and omics-related …
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Using Random Forest in the field of metabolomics
… data mining techniques, since it can be used for classification, feature extraction, and analysis. Random Forests algorithm has many different customizable parameters that affect the outcome of a particular run. Identifying the best values for these customizable attributes is a task in itself. My …
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The influence of the inclusion of biological knowledge in statistical methods to integrate multi-omics data
… unsupervised methods when solving the problem of sample classification.
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Continuous typist verification using machine learning
… feature identification and extraction, and sample classification. A dataset has been collected that is comparable in size, timing accuracy and content to others in the field, with one important exception: it is derived from real emails, rather than samples collected in an artificial setting. …
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Enhanced transcriptome profiling and biomarker discovery using meta-analytical techniques
… and as a means of classifying unknown samples. Three chapters were created to: (1) investigate three novel meta-analysis approaches as a means of combining and analyzing gene expression experiments for differential expression across experiments, (2) develop a novel meta-classification …