Free-living bacteria grown under aerobic conditions were used to investigate, by next-generation RNA sequencing analysis, the transcriptional profiles of Sinorhizobium meliloti wild-type 1021 and its derivative, RD64, overproducing the main auxin indole-3-acetic acid (IAA). Among the upregulated genes in RD64 cells, we detected the main nitrogen-fixation regulator fixJ, the two intermediate regulators fixK and nifA, and several other genes known to be FixJ targets.

Background: The DNA base composition is well known to be highly variable among organisms. Bio-physic studies on the effect of the GC increments on the DNA structure have shown that GC-richer DNA sequences are more bendable. The result was the keystone of the hypothesis proposing the metabolic rate as the major force driving the GC content variability, since an increased resistance to the torsion stress is mainly required during the transcription process to avoid DNA breakage.

Mass spectrometry is a set of technologies with many applications in characterizing biological samples. Due to the huge quantity of data, often biased and contaminated by different source of errors, and the amount of results that is possible to extract, an easy-to-learn and complete workflow is essential. GeenaR is a robust web tool for pre-processing, analysing, visualizing and comparing a set of MALDI-ToF mass spectra. It combines PHP, Perl and R languages and allows different levels of control over the parameters, in order to adapt the work to the needs and expertise of the users.

In this talk, first, we review the concept of gene-environmental interaction on the light of emerging results and the use of modern high-throughput technologies; we illustrate its impact on the understanding of complex human diseases. Then, we provide an overview of the methods available to process NGS data with particular emphasis to the detection of genomic variants, the analysis of epigenomic and transcriptional data produced by modern sequencers. Finally, we discuss how multiomic data can be used to improve our way of studying complex diseases and can provide novel research perspectives.

International initiatives such as the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) are collecting multiple datasets at different genome-scales with the aim of identifying novel cancer biomarkers and predicting survival of patients. To analyze such data, several statistical methods have been applied, among them Cox regression models. Although these models provide a good statistical framework to analyze omic data, there is still a lack of studies that illustrate advantages and drawbacks in integrating biological information and selecting groups of biomarkers.

Robust Design Optimization (RDO) represents a really interesting opportunity when the specifications of the design are careful and accurate: the possibility to optimize an industrial object for the real usage situation, improving the overall performances while reducing the risk of occurrence of off-design con- ditions, strictly depends on the availability of the information about the probability of occurrence of the various operative conditions during the lifetime of the design.

A fast algorithm related to the generalized minimal residual algorithm (GMRES) is proposed to approximate solution of a nonlinear hypersingular integral equation arising in a crack problem. At first, a collocation method is proposed and developed in weighted Sobolev space. Then, the Newton-Kantorovjch method is used for solving the obtained system of nonlinear equations.