The HADES group's main lines of research are the identification, distribution and characterization, through their structure and functions, of benthic habitats. The research lines respond to European directives such as the Marine Strategy Framework Directive (MSFD), the Habitats Directive (HD) and the Maritime Spatial Planning Directive (MSPD), collecting and analyzing the scientific information necessary for monitoring the environmental status of benthic habitats to evaluate their conservation status. Its scope of work is the infralittoral, circalittoral and bathyal zones (0-4000 m).

The main goal o fthe group is to understand how breast cancer drugs works.

The group develops research projects related to the factors and mechanisms that evaluate the effects of Marine Protected Areas as management tools for the marine environment. To achieve this, a multidisciplinary approach is adopted that ranges from taxonomy and systematics, to the biology of species, structure and dynamics of populations and benthic communities and the relationship of biological processes with environmental factors.

The group studies soil and organic waste management strategies to mitigate the impact of agricultural practices on greenhouse gas emissions (CO2, N2O and CH4). The group brings experience in the treatment and use of organic waste in agriculture as a strategy to preserve the quality of the soil and enhance its fertility, as well as in the evaluation of the environmental impact of the use of waste. The aim of the group is to improve the sustainability of agricultural systems within the context of the circular economy and promote their decarbonization as a strategy to mitigate climate change.

Ribosomes are responsible for translation of genetic information into proteins in all living organisms, and they are for example the target for about 50% of all known antibiotics in the case of the bacterial ribosome.

Our research group is focused on using computational and experimental approaches to understand and design protein functions. We have extensive experience in deep unsupervised learning and protein design, which we have applied to various projects (see below!). Over the next five years, we will expand our focus to include the design of custom-tailored and new-to-nature protein functions. This will involve machine learning and other computational approaches to explore unexplored regions of the protein space and generate novel proteins with desired functions.