A microarray configuration to quantify expression levels and relative abundance of splice variants

Over the past decade, alternative RNA splicing has raised a great interest appearing to be of high importance in the generation of expression diversity. This regulatory process plays a critical role in the normal development and its impact on the initiation and development of human disorders as well as on the pharmacological properties of drugs is increasingly being recognized. Only few studies describe specific alternative splicing expression profiling. Microarray strategies have been conceived to address alternative splicing events but with very few experimental data related to their abilities to provide true quantification values. We have developed a specific microarray configuration relying on a few, well optimized probes per splice event. Basically, five probes of 24mer are used to fully characterize a splice event. These probes are of two types, exon probes and junction probes, and are either specific to a splice event or not. The performances of such a ‘splice array’ were validated on synthetic model systems and on complex biological materials. The results indicate that DNA chips based on this design combining exon and junction derived probes enable the detection and, absolute and relative quantification of splice variants. In addition, this strategy is compatible with all the microarrays that use oligonucleotide probes

Numerical simulation of spray coalescence in an eulerian framework : direct quadrature method of moments and multi-fluid method

The scope of the present study is Eulerian modeling and simulation of polydisperse liquid sprays undergoing droplet coalescence and evaporation. The fundamental mathematical description is the Williams spray equation governing the joint number density function f(v, u; x, t) of droplet volume and velocity. Eulerian multi-fluid models have already been rigorously derived from this equation in Laurent et al. (2004). The first key feature of the paper is the application of direct quadrature method of moments (DQMOM) introduced by Marchisio and Fox (2005) to the Williams spray equation. Both the multi-fluid method and DQMOM yield systems of Eulerian conservation equations with complicated interaction terms representing coalescence. In order to validate and compare these approaches, the chosen configuration is a self-similar 2D axisymmetrical decelerating nozzle with sprays having various size distributions, ranging from smooth ones up to Dirac delta functions. The second key feature of the paper is a thorough comparison of the two approaches for various test-cases to a reference solution obtained through a classical stochastic Lagrangian solver. Both Eulerian models prove to describe adequately spray coalescence and yield a very interesting alternative to the Lagrangian solver

Large-scale Machine-Learning analysis of scientific PDF for monitoring the production and the openness of research data and software in France

There is today no standard way to reference research datasets and software in scientific communication. Emerging editorial workflows and supporting infrastructures dedicated to research datasets and software are still poorly adopted in current publishing practices and are highly fragmented. To better follow the production of research datasets and software, we present a text mining method applied to scientific publications at scale and implemented at the French national level. Our approach relies on state-of-the-art Machine Learning and document engineering techniques to ensure reliable accuracy across multiple research areas and document types. The annotations produced by our system are used by the French Open Science Monitor (BSO) platform to follow the production and the openness of research datasets and software, in the context of the second National Plan for Open Science. The source code and the data of the French Open Science Monitor, as well as all the associated tools and training data, are all available under open licences