Machine learning-based tools to model and to remove the off-target effect

A RNA interference, also called a gene knockdown, is a biological technique which consists of inhibiting a targeted gene in a cell. By doing so, one can identify statistical dependencies between a gene and a cell phenotype. However, during such a gene inhibition process, additional genes may also be modified. This is called the “off-target effect”. The consequence is that there are some additional phenotype perturbations which are “off-target”. In this paper, we study new machine learning tools that both model the cell phenotypes and remove the “off-target effect”. We propose two new automatic methods to remove the “off-target” components from a data sample. The first method is based on vector quantization (VQ). The second method we propose relies on a classification forest. Both methods rely on analyzing the homogeneity of several repetitions of a gene knockdown. The baseline we consider is a Gaussian mixture model whose parameters are learned under constraints with a standard Expectation–Maximization algorithm. We evaluate these methods on a real data set, a semi-synthetic data set, and a synthetic toy data set. The real data set and the semi-synthetic data set are composed of cell growth dynamic quantities measured in time laps movies. The main result is that we obtain the best recognition performance with the probabilistic version of the VQ-based method.     

Hydrophobin as a Nanolayer Primer That Enables the Fluorinated Coating of Poorly Reactive Polymer Surfaces

A new and simple method is presented to fluorinate the surfaces of poorly reactive hydrophobic polymers in a more environmentally friendly way using the protein hydrophobin (HFBII) as a nanosized primer layer. In particular, HFBII, via electrostatic interactions, enables the otherwise inefficient binding of a phosphate‐terminated perfluoropolyether onto polystyrene, polypropylene, and low‐density polyethylene surfaces. The binding between HFBII and the perfluoropolyether depends significantly on the environmental pH, reaching the maximum stability at pH 4. Upon treatment, the polymeric surfaces mostly retain their hydrophobic character but also acquire remarkable oil repellency, which is not observed in the absence of the protein primer. The functionalization proceeds rapidly and spontaneously at room temperature in aqueous solutions without requiring energy‐intensive procedures, such as plasma or irradiation treatments.     

Reference architectures modelling and compliance checking

Software and Systems Modeling - Reference architectures (RAs) are successfully used to represent families of concrete software architectures in several domains such as automotive, banking, and the...