ESTIMATING<i>F</i>-STATISTICS FOR THE ANALYSIS OF POPULATION STRUCTURE
Corresponding Editor: J. Felsenstein
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9,245 publications
A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood
The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction metho...
Social Network Analysis
Social network analysis is used widely in the social and behavioral sciences, as well as in economics, marketing, and industrial engineering. The social network perspective focu...
Self-Reports in Organizational Research: Problems and Prospects
Self-reports figure prominently in organizational and management research, but there are several problems associated with their use. This article identifies six categories of se...
Cluster analysis and display of genome-wide expression patterns
A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according ...
The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for Reporting Observational Studies
Much biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study's gene...
Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows
Abstract We present here a new version of the Arlequin program available under three different forms: a Windows graphical version (W inarl35 ), a console version of Arlequin ( a...
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...
New Guidelines to Evaluate the Response to Treatment in Solid Tumors
Anticancer cytotoxic agents go through a process by which their antitumor activity-on the basis of the amount of tumor shrinkage they could generate-has been investigated. In th...