A brief history of visualizing membrane systems in molecular dynamics simulations.

Understanding lipid dynamics and function, from the level of single, isolated molecules to large assemblies, is more than ever an intensive area of research. The interactions of lipids with other molecules, particularly membrane proteins, are now extensively studied. With advances in the development of force fields for molecular dynamics simulations (MD) and increases in computational resources, the creation of realistic and complex membrane systems is now common. In this perspective, we will review four decades of the history of molecular dynamics simulations applied to membranes and lipids through the prism of molecular graphics.

Statistical model choice including variable selection based on variable importance: A relevant way for biomarkers selection to predict meat tenderness.

In this paper, we describe a new computational methodology to select the best regression model to predict a numerical variable of interest Y and to select simultaneously the most interesting numerical explanatory variables strongly linked to Y. Three regression models (parametric, semi-parametric and non-parametric) are considered and estimated by multiple linear regression, sliced inverse regression and random forests. Both the variables selection and the model choice are computational. A measure of importance based on random perturbations is calculated for each covariate. The variables above a threshold are selected. Then a learning/test samples approach is used to estimate the Mean Square Error and to determine which model (including variable selection) is the most accurate. The R package modvarsel (MODel and VARiable SELection) implements this computational approach and applies to any regression datasets. After checking the good behavior of the methodology on simulated data, the R package is used to select the proteins predictive of meat tenderness among a pool of 21 candidate proteins assayed in semitendinosus muscle from 71 young bulls. The biomarkers were selected by linear regression (the best regression model) to predict meat tenderness. These biomarkers, we confirm the predominant role of heat shock proteins and metabolic ones.

An innovative approach combining Animal Performances, nutritional value and sensory quality of meat.

This work sets out a methodological approach to assess how to simultaneously control together Animal Performances, nutritional value, sensory quality of meat. Seventy-one young bulls were characterized by 97 variables. Variables of each element were arranged into either 5 homogeneous Intermediate Scores (IS) or 2 Global Indices (GI) via a clustering of variables and analysed together by Principal Component Analysis (PCA). These 3 pools of 5 IS (or 2 GI) were analysed together by PCA to established the links existing among the triptych. Classification on IS showed no opposition between Animal Performances and nutritional value of meat, as it seemed possible to identify animals with a high butcher value and intramuscular fat relatively rich in polyunsaturated fatty acids. Concerning GI, the classification indicated that Animal Performances were negatively correlated with sensory quality. This method appeared to be a useful contribution to the management of animal breeding for an optimal trade-off between the three elements of the triptych.

Taxonomy of gymnospermae: multivariate analyses of leaf fatty acid composition.

The fatty acid composition of photosynthetic tissues from 137 species of gymnosperms belonging to 14 families was determined by gas chromatography. Statistical analysis clearly discriminated four groups. Ginkgoaceae, Cycadaceae, Stangeriaceae, Zamiaceae, Sciadopityaceae, Podocarpaceae, Cephalotaxaceae, Taxaceae, Ephedraceae and Welwitschiaceae are in the first group, while Cupressaceae and Araucariaceae are mainly in the second one. The third and the fourth groups composed of Pinaceae species are characterized by the genera Larix, and Abies and Cedrus, respectively. Principal component and discriminant analyses and divisive hierarchical clustering analysis of the 43 Pinaceae species were also performed. A clear-cut separation of the genera Abies, Larix, and Cedrus from the other Pinaceae was evidenced. In addition, a mass analysis of the two main chloroplastic lipids from 14 gymnosperms was performed. The results point to a great originality in gymnosperms since in several species and contrary to the angiosperms, the amount of digalactosyldiacylglycerol exceeds that of monogalactosyldiacylglycerol.