Analyzing longitudinal microbial metabolomics data

A longitudinal experimental design in combination with metabolomics and multiway data analysis is a powerful approach in the identification of metabolites whose correlation with bioproduct formation shows a shift in time. In this paper, a strategy is presented for the analysis of longitudinal microbial metabolomics data, which was performed in...

Matrix correlations for high-dimensional data: The modified RV-coefficient

Motivation: Modern functional genomics generates high-dimensional datasets. It is often convenient to have a single simple number characterizing the relationship between pairs of such high-dimensional datasets in a comprehensive way. Matrix correlations are such numbers and are appealing since they can be interpreted in the same way as Pearson's...

Metabolic profiling of the response to an oral glucose tolerance test detects subtle metabolic changes.

BACKGROUND: The prevalence of overweight is increasing globally and has become a serious health problem. Low-grade chronic inflammation in overweight subjects is thought to play an important role in disease development. Novel tools to understand these processes are needed. Metabolic profiling is one such tool that can provide novel insights into...

The effect of Korean pine nut oil on in vitro CCK release, on appetite sensations and on gut hormones in post-menopausal overweight women

Appetite suppressants may be one strategy in the fight against obesity. This study evaluated whether Korean pine nut free fatty acids (FFA) and triglycerides (TG) work as an appetite suppressant. Korean pine nut FFA were evaluated in STC-1 cell culture for their ability to increase cholecystokinin (CCK-8) secretion vs. several other dietary...

How to distinguish healthy from diseased? Classification strategy for mass spectrometry-based clinical proteomics

SELDI-TOF-MS is rapidly gaining popularity as a screening tool for clinical applications of proteomics. Application of adequate statistical techniques in all the stages from measurement to information is obligatory. One of the statistical methods often used in proteomics is classification: the assignment of subjects to discrete categories, for...

Assessing the performance of statistical validation tools for megavariate metabolomics data

Statistical model validation tools such as cross-validation, jack-knifing model parameters and permutation tests are meant to obtain an objective assessment of the performance and stability of a statistical model. However, little is known about the performance of these tools for megavariate data sets, having, for instance, a number of variables...

Risk estimation for carcinogens based on epidemiological data: A structured approach, illustrated by an example on chromium

It is generally recognized that human, epidemiological data, if available, are preferred as the starting point for quantitative risk analysis above the use of data from animal studies. Although methods to obtain proper risk estimates from epidemiological data are available, several impediments prevent their widespread application. These...

Validation and sensitivity analysis of probabilistic models of dietary exposure to micronutrients: An example based on vitamin B6

Probabilistic modelling can be used to get an insight into the variability and uncertainty of the nutrient intake in a population. When a probabilistic model is used, it is important that it is validated. Furthermore, a sensitivity analysis of the model output can give an insight into the most important input variables of the model and can be...