Pages that link to "Item:Q77768"

The following pages link to Statistical Applications in Genetics and Molecular Biology (Q77768):

Displaying 50 items.

• Calculating confidence intervals for prediction error in microarray classification using resampling (Q2863958) (← links)
• Structure learning in nested effects models (Q2863959) (← links)
• Correcting the estimated level of differential expression for gene selection bias: application to a microarray study (Q2863960) (← links)
• Adapting prediction error estimates for biased complexity selection in high-dimensional bootstrap samples (Q2863961) (← links)
• Adaptive choice of the number of bootstrap samples in large scale multiple testing (Q2863962) (← links)
• Re-cracking the nucleosome positioning code (Q2863963) (← links)
• Semi-parametric differential expression analysis via partial mixture estimation (Q2863964) (← links)
• A SNP streak model for the identification of genetic regions identical-by-descent (Q2863966) (← links)
• Detecting two-locus gene-gene effects using monotonisation of the penetrance matrix (Q2863969) (← links)
• Modeling DNA methylation in a population of cancer cells (Q2863970) (← links)
• Phenotyping genetic diseases using an extension of \(\mu\)-scores for multivariate data (Q2863973) (← links)
• The estimator of the optimal measure of allelic association: mean, variance and probability distribution when the sample size tends to infinity (Q2863975) (← links)
• Predicting protein concentrations with ELISA microarray assays, monotonic splines and Monte Carlo simulation (Q2863980) (← links)
• A comparison of normalization techniques for microRNA microarray data (Q2863984) (← links)
• Collapsing SNP genotypes in case-control genome-wide association studies increases the type I error rate and power (Q2863986) (← links)
• Estimating number of clusters based on a general similarity matrix with application to microarray data (Q2863987) (← links)
• Data distribution of short oligonucleotide expression arrays and its application to the construction of a generalized intellectual framework (Q2863989) (← links)
• Approximately sufficient statistics and Bayesian computation (Q2863990) (← links)
• A composite-conditional-likelihood approach for gene mapping based on linkage disequilibrium in windows of marker loci (Q2863991) (← links)
• Statistical methods in integrative analysis for gene regulatory modules (Q2863993) (← links)
• Reducing spatial flaws in oligonucleotide arrays by using neighborhood information (Q2863995) (← links)
• Pattern classification of phylogeny signals (Q2863996) (← links)
• A unification of multivariate methods for meta-analysis of genetic association studies (Q2863997) (← links)
• Importance sampling for the infinite sites model (Q2863998) (← links)
• Supervised distance matrices (Q2863999) (← links)
• Addressing the shortcomings of three recent Bayesian methods for detecting interspecific recombination in DNA sequence alignments (Q2864001) (← links)
• A sparse PLS for variable selection when integrating omics data (Q2864004) (← links)
• TRAB: testing whether mutation frequencies are above an unknown background (Q2864006) (← links)
• Case-control breast cancer study of MALDI-TOF proteomic mass spectrometry data on serum samples (Q2864011) (← links)
• Organizing a competition on clinical mass spectrometry based proteomic diagnosis (Q2864012) (← links)
• Developing a discrimination rule between breast cancer patients and controls using proteomics mass spectrometric data: a three-step approach (Q2864014) (← links)
• Principal component discriminant analysis (Q2864015) (← links)
• Classification of breast cancer versus normal samples from mass spectrometry profiles using linear discriminant analysis of important features selected by random forest (Q2864016) (← links)
• A classification model for the Leiden proteomics competition (Q2864018) (← links)
• Empirical Bayes logistic regression (Q2864020) (← links)
• Autocorrelated logistic ridge regression for prediction based on proteomics spectra (Q2864021) (← links)
• Support vector machine approach to separate control and breast cancer serum samples (Q2864022) (← links)
• A cross-validation study to select a classification procedure for clinical diagnosis based on proteomic mass spectrometry (Q2864025) (← links)
• Assessing the validity domains of graphical Gaussian models in order to infer relationships among components of complex biological systems (Q2864028) (← links)
• Breast cancer diagnosis from proteomic mass spectrometry data: a comparative evaluation (Q2864029) (← links)
• Sparse canonical correlation analysis with application to genomic data integration (Q2864031) (← links)
• Orthology-based multilevel modeling of differentially expressed mouse and human gene pairs (Q2864033) (← links)
• Sequential analysis for microarray data based on sensitivity and meta-analysis (Q2864034) (← links)
• Dimension reduction of microarray data in the presence of a censored survival response: a simulation study (Q2864036) (← links)
• A nonlinear mixed-effects model for estimating calibration intervals for unknown concentrations in two-color microarray data with spike-ins (Q2864039) (← links)
• Composite likelihood modeling of neighboring site correlations of DNA sequence substitution rates (Q2864041) (← links)
• A multiple testing approach to high-dimensional association studies with an application to the detection of associations between risk factors of heart disease and genetic polymorphisms (Q2864044) (← links)
• Hypothesis tests for point-mass mixture data with application to 'omics data with many zero values (Q2864046) (← links)
• Inferring dynamic genetic networks with low order independencies (Q2864047) (← links)
• Normalization method for transcriptional studies of heterogeneous samples -- simultaneous array normalization and identification of equivalent expression (Q2864050) (← links)