This school is designed in priority for biologists and bio-informaticians (completing a PhD degree or currently post-doctoral fellows, as well as researchers), who wish to learn the bases of network analyses.
The main aims (regarding various types of networks, the relevance of their analyses, and some bases in graph theory) will be introduced by short theoretical classes, followed by practical case-studies, introducing the basics in programming required to run such network analyses as well as to use the existing software/tools. The goal is that, by the end of this summer school, all applicants will be qualified to perform network analyses of their own datasets.
More precisely, the focus will be on the following concepts and methods:
- Introgressive evolution and large-scale diversity studies.
- Construction and analysis of sequence similarity networks
(construction and sorting of connected components, definition of gene
families, search for composite genes, implementation of centrality measures)
- Construction and analysis of genome networks (construction of
weighted genome networks, implementation of their diameter, shortest
paths, analyses of labeled nodes, etc.)
- Construction and analysis of gene-genome bipartite graphs (detection
of connected components, and their articulation points, and twins)
In addition, 9 conferences on networks and evolution will be delivered by leading scientists during this school. Expected speakers will be announced later.