Publications

Density Estimation for Statistics and Data Analysis

Introduction. Survey of Existing Methods. The Kernel Method for Univariate Data. The Kernel Method for Multivariate Data. Three Important Methods. Density Estimation in Action.

RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models

Abstract Summary: RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a sequential and parallel program for inference of large phylogenies ...

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Training Deep Neural Networks is complicated by the fact that the distribution of each layer's inputs changes during training, as the parameters of the previous layers change. T...

GROMACS 4:  Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation

Molecular simulation is an extremely useful, but computationally very expensive tool for studies of chemical and biomolecular systems. Here, we present a new implementation of o...

Fast, scalable generation of high‐quality protein multiple sequence alignments using Clustal Omega

Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal

The cBioPortal enables integration, visualization, and analysis of multidimensional cancer genomic and clinical data.

Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers

Community structure in social and biological networks

A number of recent studies have focused on the statistical properties of networked systems such as social networks and the Worldwide Web. Researchers have concentrated particula...

Mastering the game of Go with deep neural networks and tree search

Parallel Distributed Processing

What makes people smarter than computers? These volumes by a pioneering neurocomputing group suggest that the answer lies in the massively parallel architecture of the human min...

Multiresolution gray-scale and rotation invariant texture classification with local binary patterns

Presents a theoretically very simple, yet efficient, multiresolution approach to gray-scale and rotation invariant texture classification based on local binary patterns and nonp...

Tissue-based map of the human proteome

Protein expression across human tissues Sequencing the human genome gave new insights into human biology and disease. However, the ultimate goal is to understand the dynamic exp...