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Showing 1 to 7 of 7 for “"Sample classification"”.

  1. 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 …

    vt Repository record for Statistical Analysis of Gene Expression Profile: Transcription Network Inference and Sample Classification (opens in a new tab)

  2. 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 …

    unm Repository record for Analyzing geological materials under martian conditions using laser-induced breakdown spectroscopy : plasma fundamentals, sample classification, and trace element quanitification (opens in a new tab)

  3. 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 …

    purdue-thes Repository record for Signal enhancement and data mining for biological and chemical samples using mass spectrometry (opens in a new tab)

  4. 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 …

    rowan Repository record for Using Random Forest in the field of metabolomics (opens in a new tab)

  5. 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. …

    waikato-masters Repository record for Continuous typist verification using machine learning (opens in a new tab)

  6. 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

    uiuc Repository record for Enhanced transcriptome profiling and biomarker discovery using meta-analytical techniques (opens in a new tab)