Gene set analysis methods are widely used to provide insight into high-throughput gene
expression data. There are many gene set analysis methods available. These methods rely …

Background Many high-throughput experiments compare two phenotypes such as disease
vs. healthy, with the goal of understanding the underlying biological phenomena …

Functional enrichment analysis has played a key role in the biological interpretation of high-
throughput omics data. As a long-standing and widely used web application for functional …

There are only a few platforms that integrate multiple omics data types, bioinformatics tools,
and interfaces for integrative analyses and visualization that do not require programming …

Statistical methods for enrichment analysis are important tools to extract biological
information from omics experiments. Although these methods have been widely used for the …

Methodological breakthroughs over the past four decades have repeatedly revolutionized
transcriptome profiling. Using RNA sequencing (RNA-seq), it has now become possible to …

Pathway analysis is a set of widely used tools for research in life sciences intended to give
meaning to high-throughput biological data. The methodology of these tools settles in the …

Metabolomics is a rapidly growing field consisting of the analysis of a large number of
metabolites at a system scale. The two major goals of metabolomics are the identification of …

Motivation: Recent advances in high-throughput omics technologies have enabled
biomedical researchers to collect large-scale genomic data. As a consequence, there has …

Motivation Although gene set enrichment analysis has become an integral part of high-
throughput gene expression data analysis, the assessment of enrichment methods remains …