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.
Non-canonical nucleotides are widespread chemical modifications in eukaryotic genomes and transcriptomes, especially within the epitranscriptome. Traditional enrichment-based sequencing methods cannot detect them at single-molecule resolution, a limitation overcome by nanopore sequencing. Researchers from the University of Bari (Italy) present a transformer-based model for the ab initio detection of multiple RNA modifications, along with two tools, NanoListener and NanoSpeech, to create training datasets and develop modification-aware basecallers. Their approach enables the simultaneous identification of up to nine ribonucleotide variants.
Protein embeddings encode sequence information using protein language models. The Embedding-Based Alignment (EBA) method enables pairwise embedding comparison and remote homolog detection. In this paper we show that, when applied to a set of multifunctional human proteins, EBA identifies remote homologs sharing structural and functional features, validated on the Swiss-Prot database.
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.