We summarise various ways of performing dimensionality reduction on high‐dimensional
microarray data. Many different feature selection and feature extraction methods exist and …

Powerful specialized software is essential for managing, quantifying, and ultimately deriving
scientific insight from results of a microarray experiment. We have developed a suite of …

Data-driven discovery is revolutionizing how we model, predict, and control complex
systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and …

Background Immunosuppressive and anti-cytokine treatment may have a protective effect for
patients with COVID-19. Understanding the immune cell states shared between COVID-19 …

As a promising way for analyzing data, sparse modeling has achieved great success
throughout science and engineering. It is well known that the sparsity/low-rank of a …

Motivation: Gene expression microarray experiments can generate data sets with multiple
missing expression values. Unfortunately, many algorithms for gene expression analysis …

BioTechniques 34: 374-378 (February 2003) supported, MADAM is being adapted to read
and write MAGE-ML, the XML data exchange format being developed by an international …

Motivation Single-cell RNA-seq makes possible the investigation of variability in gene
expression among cells, and dependence of variation on cell type. Statistical inference …

Comprehensive analysis of the gene expression profiles associated with human monocyte-
to-macrophage differentiation and polarization toward M1 or M2 phenotypes led to the …

One of the challenges of bioinformatics is to develop effective ways to analyze global gene
expression data. A rigorous approach to gene expression analysis must involve an up-front …