Statistical Analysis of Gene Expression Microarray Data

2003

365 citations recorded by the source corpus.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/d1c75829aac81a1f735a128bd5957a065558f5e1

Citations in the corpus

• Analysis of Gene Expression Data Using BRB-Array Tools (2007, neutral): “The models provided include diagonal linear discriminant analysis (Dudoit and Fridlyand, 2003), compound covariate predictor (Radmacher et al., 2002), nearest neighbor classification (Ripley, 1996), nearest centroid classification, shrunken centroid classification (Tibshirani et al., 2002), support…”
• Goodness-of-fit testing and quadratic functional estimation from indirect observations (2006, neutral): “BY CRISTINA BUTUCEA”
• Simple decision rules for classifying human cancers from gene expression profiles (2005, neutral): “However the performance of a gene selection method may depend on the nature of the classifier, the criterion for selection and the number of genes selected (Dudoit and Fridlyand, 2003; Li et al. , 2004).”
• SMOTE for high-dimensional class-imbalanced data (2013, neutral): “The (uncorrected) classifiers trained on low-dimensional class-imbalanced data assigned most of the samples to the majority class, both in null and in alternative case (Figure 2); the classifiers with the smallest bias towards the majority class were DLDA (not biased in the alternative case) and DQDA,”
• Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments (2004, neutral): “Keywords: microarrays, empirical Bayes, linear models, hyperparameters, differential expression”
• Use of within-array replicate spots for assessing differential expression in microarray experiments (2005, neutral): “Foreground intensities were background corrected using the ‘morph’ background measure and the scorecard spot log-ratios were normalized using global loess normalization with the default smoothing span of 0.3 (Yang et al., 2001; Smyth and Speed, 2003).”