ELIXIR has released three new onboarding videos developed through the PeoplePulse Commissioned Service. In the video dedicated to industry engagement, Francesca De Leo, Deputy Head of Node of ELIXIR Italy, shares ELIXIR-IT’s experience and initiatives to strengthen collaboration between research and industry.
A new video from the ELIXIR-IT 2026 meeting features key experts discussing the vital role of research infrastructures, data sharing, and PNRR-funded innovation in Italian life sciences.
The ELIXIR-IT 2026 meeting in Bari focused on omics, AI, and data sharing, strengthening Italy's strategic role in life sciences research.
The new ELIXIR-IT website features a structural overhaul with integrated omics and ICT services, improved interoperability, and new Industry and Impact sections.
ELIXIR adds 6 Core Data Resources and 2 Deposition Databases, reaching 37 and 17 total. These trusted tools support long-term life science research in Europe.
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.