The event in Bari brought together academia and biotech industry. It highlighted ELIXIR-IT's role in fostering collaboration and innovation in the life sciences.
ELIXIR-IT is collaborating with Researchalize, a platform connecting biomedical researchers in Italy. It facilitates networking, knowledge sharing, and access to resources, funding and the latest research topics.
BBMRI.it and ELIXIR-IT are collaborating to advance biomedical research and precision medicine in Italy by integrating bioinformatics and biobanking.
ELIXIR-IT and Scientifica Venture Capital are partnering to accelerate technology transfer in life sciences. This collaboration will support startups by combining scientific expertise with investment and lab access.
Confindustria Bari-Bat and ELIXIR-IT have partnered to boost biotech innovation and training in Puglia. The collaboration leverages ELIXIR-IT's advanced genomic tools to support companies.
CREDO, a Customizable, REproducible, DOcker file generator for bioinformatics applications, has been developed as a tool to moderate reproducibility issues by building and distributing docker containers with embedded bioinformatics tools. CREDO simplifies the process of generating Docker images, facilitating reproducibility and efficient research in bioinformatics.
In this work, it is evaluated the possibility of improving AlphaFold2’s three-dimensional predictions by developing a new pipeline (AlphaMod) that integrates AlphaFold2 with MODELLER, a traditional homology modeling program. For this study, MARCONI100 at HPC@CINECA was used, which was made available through an ELIXIR project.
In this study, we explored the link between gut impairment and severe COVID-19 in people with HIV (PWH). We compared PWH with COVID-19 to HIV-uninfected individuals hospitalized for the same condition. Despite more severe clinical symptoms in PWH, we did not observe significant differences in gut barrier dysfunction markers between the two groups.
Recent years have seen a substantial increase in RNA-seq data production, with this technique becoming the primary approach for gene expression studies across a wide range of non-model organisms. The majority of these organisms lack a well-annotated reference genome to serve as a basis for studying differentially expressed genes (DEGs).