Densely Connected Convolutional Networks
Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to ...
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<tt>edgeR</tt> : a Bioconductor package for differential expression analysis of digital gene expression data
Abstract Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics a...
XGBoost
Tree boosting is a highly effective and widely used machine learning method.\nIn this paper, we describe a scalable end-to-end tree boosting system called\nXGBoost, which is use...
Three Approaches to Qualitative Content Analysis
Content analysis is a widely used qualitative research technique. Rather than being a single method, current applications of content analysis show three distinct approaches: con...
LIBSVM
LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this package since the year 2000. The goal is to help users to easily apply SVM to their...
A power primer.
One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard mate...
Highly accurate protein structure prediction with AlphaFold
Abstract Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort ...
limma powers differential expression analyses for RNA-sequencing and microarray studies
© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. limma is an R/Bioconductor software package that provides an integrated solution ...