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Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here...
Bias in meta-analysis detected by a simple, graphical test
A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses ...
Density-functional exchange-energy approximation with correct asymptotic behavior
Current gradient-corrected density-functional approximations for the exchange energies of atomic and molecular systems fail to reproduce the correct 1/r asymptotic behavior of t...
The CES-D Scale
The CES-D scale is a short self-report scale designed to measure depressive symptomatology in the general population. The items of the scale are symptoms associated with depress...
Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks
Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified con...
Regression Shrinkage and Selection Via the Lasso
SUMMARY We propose a new method for estimation in linear models. The ‘lasso’ minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients b...
Genetic algorithms in search, optimization, and machine learning
From the Publisher: This book brings together - in an informal and tutorial fashion - the computer techniques, mathematical tools, and research results that will enable both st...
A new look at the statistical model identification
The history of the development of statistical hypothesis testing in time series analysis is reviewed briefly and it is pointed out that the hypothesis testing procedure is not a...
Maximum Likelihood from Incomplete Data Via the <i>EM</i> Algorithm
Summary A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone ...