Increased availability of high-throughput technologies has generated an ever-growing
number of omics data that seek to portray many different but complementary biological …

To study complex biological processes holistically, it is imperative to take an integrative
approach that combines multi-omics data to highlight the interrelationships of the involved …

With the rapid adoption of high-throughput omic approaches to analyze biological samples
such as genomics, transcriptomics, proteomics, and metabolomics, each analysis can …

We present the R package missMDA which performs principal component methods on
incomplete data sets, aiming to obtain scores, loadings and graphical representations …

Despite many years of research, no biomarkers for stroke are available to use in clinical
practice. Progress in high-throughput technologies has provided new opportunities to …

State-of-the-art next-generation sequencing, transcriptomics, proteomics and other high-
throughput 'omics' technologies enable the efficient generation of large experimental data …

Multiple factor analysis (MFA, also called multiple factorial analysis) is an extension of
principal component analysis (PCA) tailored to handle multiple data tables that measure …

A decade ago, the Gene Expression Omnibus (GEO) database was established at the
National Center for Biotechnology Information (NCBI). The original objective of GEO was to …

High-throughput technologies have been used to generate a large amount of omics data. In
the past, single-level analysis has been extensively conducted where the omics …

This protocol describes an analytical platform for the analysis of intra-and extracellular
metabolites of microbial cells (yeast, filamentous fungi and bacteria) using gas …