Biostatistics

Metabolism is the whole of all chemical processes in a living organism. These processes ensure that the organism grows and is resistant to changes in the environment. Metabolites are grouped in sequences of subsequent metabolic processes, called metabolic pathways, which are connected to each other in a large network. The study of metabolic pathways is important for various disciplines in scientific research and industry, including medicine, pharmacy and food industry.

In this paper, we demonstrate the use of two-mode clustering for genotype by trait and genotype by environment data. In contrast to two separate (one mode) clusterings on genotypes or traits/environments, two-mode clustering simultaneously produces homogeneous groups of genotypes and traits/environments. For two-mode clustering, we first scan all two-mode cluster solutions with all possible numbers of clusters using k-means. After deciding on the final numbers of clusters, we continue with a two-mode clustering algorithm based on a genetic algorithm.

Stable Foxp3 expression is required for the development of functional regulatory T (Treg) cells. Here, we demonstrate that the expression of the transcription factor Foxp3 can be regulated through the polyubiquitination of multiple lysine residues, resulting in proteasome-mediated degradation.

MOTIVATION:

Metabolomics and other omics tools are generally characterized by large data sets with many variables obtained under different environmental conditions. Clustering methods and more specifically two-mode clustering methods are excellent tools for analyzing this type of data. Two-mode clustering methods allow for analysis of the behavior of subsets of metabolites under different experimental conditions. In addition, the results are easily visualized.

ANOVA–simultaneous component analysis (ASCA) is a recently developed tool to analyze multivariate data. In this paper, we enhance the explorative capability of ASCA by introducing a projection of the observations on the principal component subspace to visualize the variation among the measurements. We compare the significance of experimental effects for ASCA and ANOVA–principal component analysis (PCA), a similar tool to explore multivariate data, by using permutation tests.

In the present study, a novel method of measuring the uptake of nutrients by 1H NMR spectroscopy was performed to determine dietary effects.