Publications

ImageNet: A large-scale hierarchical image database

The explosion of image data on the Internet has the potential to foster more sophisticated and robust models and algorithms to index, retrieve, organize and interact with images...

Fast gapped-read alignment with Bowtie 2

Gradient-based learning applied to document recognition

Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based learning technique. Given an appropriate networ...

Distinctive Image Features from Scale-Invariant Keypoints

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...

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...

Designing complex, dynamic yet multi-functional materials and devices is challenging because the design spaces for these materials have numerous interdependent and often conflic...

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 ...