Statistics

• Validation of experimental results against models.
• Combined use of regressions and representation methods to extract relationships.
• Use of the bootstrap method.
• Modelling of biological experiments.

Bioinformatics

• Performing of NGS analysis, including setting up pipelines.
• Use of multiple biological databases and genome browsers.
• Setting up of specific biological database.
• Analysis of sequences, including multiple alignment and motif finding.
• Inference of phylogenetic histories.
• Good knowledge of biological networks.

Programming

• Use of standard algorithms and data structures.
• Day-to-day use of Python for scientific tasks, using numpy, scipy, matplotlib.
• Day-to-day use of Bash for scripts automation, using hastables and GNU parallel.
• Good knownledge of Perl, Java, C, Rust and R.

Computing

• Day-to-day use of Linux, for desktop ( Ubuntu and Manjaro) as well as for server ( CentOS and Debian).
• Use of computing clusters (SGE like).
• Good knowledge of databases systems, both relational ( SQLite and MySQL) and NoSQL (graph database with Neo4J or dgraph, and document database CouchDB).

Communication

• Scientific writing and talks.
• Popularisation
• Teaching