The INEXTVIR project will allow us to have a better understanding on plant viruses on the scientific side and will provide more knowledge on the social and economic impact of those viruses. That mean that the scientific improvement that I will produce are going to be used in real life situation.
I am working on improving virus detection in plant data, I hope to achieve two level of improvement. On one hand, the goal is to monitor more closely plant-virus presence in Europe by making the bio-informatic detection faster and more efficient in a way that is easy to use by the laboratories. On the other hand, the detection must be more precise to help researcher and biologist make further discovery on those viruses.
The combination of the two type of improvement will help raise the global knowledge about virus, which bring us closer to food sustainability.
I Adapt and apply validation protocols for existing bioinformatic pipelines to detect viruses from HTS datasets
II Evaluate the ability to identify Single Nucleotide Polymorphisms (SNP) in virus genomes from HTS datasets and propose relevant guidelines
III Develop new diagnostic tests for important virus based on in silico analysis of HTS results from the project and organize an inter-laboratory evaluation of at least one test (for the virus with highest socio-economic importance)