The annotation of transcription binding sites in new sequenced genomes is an important and challenging problem. We have previously shown how a regression model that linearly relates gene expression levels to the matching scores of nucleotide patterns allows us to identify DNA-binding sites from a collection of co-regulated genes and their nearby non-coding DNA sequences. Our methodology uses Bayesian models and stochastic search techniques to select transcription factor binding site candidates. Here we show that this methodology allows us to identify binding sites in nearby species. We present examples of annotation crossing from Schizosaccharomyces pombe to Schizosaccharomyces japonicus. We found that the eng1 motif is also regulating a set of 9 genes in S. japonicus. Our framework may have an effective interest in conveying information in the annotation process of a new species. Finally we discuss a number of statistical and biological issues related to the identification of binding sites through covariates of genes expression and sequences.
A thin plate ? has an inaccessible side in contact with aggressive external agents. On the other side we are able to heat the plate and take temperature maps (thermal data) in laboratory conditions. Detecting and evaluating damages on the inaccessible side from thermal data requires the solution of a nonlinear inverse problem for the heat equation. To do this, it is extremely important to assign correct boundary conditions, in particular on the inaccessible boundary of ?. In several cases the boundary conditions must take account of heat exchange between ? and the environment. Here we discuss, from the quantitative point of view, the relation between the physical constants of the system (conductivity, width of the plate, ...) and the heat transfer through the boundary of ?.
inverse problems
thermography
Biot number
Robin boundary conditions
Quantifying trace gas emissions and the influence of surface exchange processes on the atmosphere is a necessary step towards the control of global greenhouse gas emissions. Also air quality models require highly resolved emission data. This paper propose a procedure based on the mass balance method and implemented on highly resolved aircraft data, which allows us to estimate surface exchanges on areas of several km 2 and heterogeneous surface features. We adopt a nonparametric approach and reconstruct the fluxes on the surface of a virtual box surrounding the area of interest using Shepard functions. Two different techniques are also proposed to face lack of data on the top surface of the box. The method is applied to the experimental data from a measurement campaign in Eboli to obtain an evaluation of the CO2 emission/absorption in the area.
