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Partners: Institut Laue-Langevin, European Synchrotron Radiation Facility, EGI Foundation

Project description

Small-angle scattering techniques are used to determine the shape, distribution, and uniformity of particles in solution, with a large domain of applications concerning biological macromolecules. New developments and faster acquisition also allow for tracking the dynamics of the particles themselves. Small-Angle X-ray or Neutron Scattering (SAXS or SANS, respectively) can be very effective tools for studying, for example, the time dependence of genome release from phages, investigating entire viral life cycles, or the assembly of macromolecular complexes, providing deep insights into infection pathways. Furthermore, neutrons and X-rays can be applied in a complementary mode, resulting in a much more accurate and detailed characterization of biological systems.

However, this approach is still rare though, due to a lack of appropriate platforms, infrastructures, and FAIR data. This project aims to advance medical research by providing an EOSC-based platform that enables FAIR data and software, leading-edge processing pipelines. This will support reproducibility and automated validation, and will allow integration with other relevant structural databases.

Societal challenge

Neutron and synchrotron experiments are expensive. However, the collected data are usually exploited only by a small experimental team performing a particular experiment. In addition,  the analysis of the data requires often sophisticated tools together with a large domain-specific knowledge, restricting the utility to a restricted community of scattering experts. This should be improved by providing a platform allowing the easy reuse of expensive data sets collected at large scale neutron and synchrotron facilities to explore the conformations of proteins, enzymes and other large macromolecular complexes.

Technical challenge

The analysis of neutron and x-ray small angle scattering data for biological macromolecules require a large degree of domain-specific knowledge and the use of several specialized software tools, not always easy to install and use, combined in a complex workflow. The project aimed to provide a series of simple to use Jupyter notebooks, with the needed software already installed, and default parameters and easy to follow instructions to facilitate such analysis. Additionally, the databases of the two partners, ESRF (https://data.esrf.fr) an ILL (https://data.ill.fr), will provide access to the experimental data collected in both facilities.

The EOSC Future added value

Main results

Other resources


Service: http://replay.notebooks.egi.eu + https://github.com/isafiulina/sas_helper