The availability of good quality prediction models is essential to deal with the ever-growing world’s complexity. Indeed, being able to make accurate predictions regarding the appearance of strains that are resistant to antibiotics before they increase in frequency can greatly extend the life of the available antibiotics. Moreover, predicting which COVID-19 strain has the potential to replace the presently dominant one gives us time to prepare for such an event, while the development of new drugs requires a detailed understanding of the molecular basis of the disease phenotype. The same is true when trying to select for any trait with economical value. The Phenotypic Evolution group at i3S blends bioinformatics, biostatistics, 3D structure modeling, genomics, transcriptomics, evolutionary biology and population genetics to produce prediction models that can help answer the above questions. The evolutionary biology and populations genetics know-how of the group allows a deeper understanding of the behavior of biological systems since, as Theodosius Dobzhansky stated “Nothing in Biology makes sense except in the light of evolution", and as remarked by Michael Lynch “Nothing in evolutionary biology makes sense except in the light of population genetics”. The bioinformatics, biostatistics, and –omics expertise allow the development of software pipelines that can be used to analyze the ever-growing biological datasets in a relatively short amount of time, thus providing useful answers. Such diverse know-how is the result of the integration of researchers from two different IBMC research groups (Molecular Evolution and Evolutionary Systems Biology).
The bioinformatics tools and models developed by us are often general and thus, they are available at the pegi3S Bioinformatics Docker Images project, where more than 77 commonly used software applications, pipelines, and software for the automated submission to web servers can be found. This set of tools has been recognized by ELIXIR as a service (https://elixireurope.org/services). These tools have been used to answer questions related to the evolution of genes underlying phenotypes of medical and economical importance, to identify the amino acids sites determining phenotypic differences, as well as inferring how protein-protein interactions change during evolution. At present, we are working on the molecular basis of Mycobacterium antibiotic resistance, the molecular basis of COVID-19 pathogenicity, and the identification of useful protein targets for the development of new drugs to treat neurodegenerative disorders. As a member of DrosEU, we are also working on the most complete characterization of nucleotide (at the genome level), chromosomal and phenotypic variation of European Drosophila melanogaster populations. We are also studying the evolution of vitamin C synthesis in animals, and protein co-evolution using the plant breeding system as a model, among others. For a full view of the research developed by us refer to our ORCID page.