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Carlos Eduardo Ribas

European Bioinformatics Institute

ORCID: 0000-0002-9572-273X

Publishes on RNA modifications and cancer, RNA and protein synthesis mechanisms, RNA Research and Splicing. 19 papers and 639 citations.

19Publications
639Total Citations

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Top publicationsby citations

RNAcentral 2021: secondary structure integration, improved sequence search and new member databases
Blake Sweeney, Anton I. Petrov, Carlos Eduardo Ribas et al.|Nucleic Acids Research|2020
Cited by 412Open Access

RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences that provides a single access point to 44 RNA resources and >18 million ncRNA sequences from a wide range of organisms and RNA types. RNAcentral now also includes secondary (2D) structure information for >13 million sequences, making RNAcentral the world's largest RNA 2D structure database. The 2D diagrams are displayed using R2DT, a new 2D structure visualization method that uses consistent, reproducible and recognizable layouts for related RNAs. The sequence similarity search has been updated with a faster interface featuring facets for filtering search results by RNA type, organism, source database or any keyword. This sequence search tool is available as a reusable web component, and has been integrated into several RNAcentral member databases, including Rfam, miRBase and snoDB. To allow for a more fine-grained assignment of RNA types and subtypes, all RNAcentral sequences have been annotated with Sequence Ontology terms. The RNAcentral database continues to grow and provide a central data resource for the RNA community. RNAcentral is freely available at https://rnacentral.org.

R2DT is a framework for predicting and visualising RNA secondary structure using templates
Blake Sweeney, David Hoksza, Eric P. Nawrocki et al.|Nature Communications|2021
Cited by 147Open Access

Non-coding RNAs (ncRNA) are essential for all life, and their functions often depend on their secondary (2D) and tertiary structure. Despite the abundance of software for the visualisation of ncRNAs, few automatically generate consistent and recognisable 2D layouts, which makes it challenging for users to construct, compare and analyse structures. Here, we present R2DT, a method for predicting and visualising a wide range of RNA structures in standardised layouts. R2DT is based on a library of 3,647 templates representing the majority of known structured RNAs. R2DT has been applied to ncRNA sequences from the RNAcentral database and produced >13 million diagrams, creating the world's largest RNA 2D structure dataset. The software is amenable to community expansion, and is freely available at https://github.com/rnacentral/R2DT and a web server is found at https://rnacentral.org/r2dt .

R2DT: a comprehensive platform for visualizing RNA secondary structure
Holly McCann, Caeden D. Meade, Loren Dean Williams et al.|Nucleic Acids Research|2025
Cited by 22Open Access

RNA secondary (2D) structure visualization is an essential tool for understanding RNA function. R2DT is a software package designed to visualize RNA 2D structures in consistent, recognizable, and reproducible layouts. The latest release, R2DT 2.0, introduces multiple significant features, including the ability to display position-specific information, such as single nucleotide polymorphisms or SHAPE reactivities. It also offers a new template-free mode allowing visualization of RNAs without pre-existing templates, alongside a constrained folding mode and support for animated visualizations. Users can interactively modify R2DT diagrams, either manually or using natural language prompts, to generate new templates or create publication-quality images. Additionally, R2DT features faster performance, an expanded template library, and a growing collection of compatible tools and utilities. Already integrated into multiple biological databases, R2DT has evolved into a comprehensive platform for RNA 2D visualization, accessible at https://r2dt.bio.

Exploring Non‐Coding RNAs in RNAcentral
Blake Sweeney, Arina A. Tagmazian, Carlos Eduardo Ribas et al.|Current Protocols in Bioinformatics|2020
Cited by 17Open Access

Non-coding RNAs are essential for all life and carry out a wide range of functions. Information about these molecules is distributed across dozens of specialized resources. RNAcentral is a database of non-coding RNA sequences that provides a unified access point to non-coding RNA annotations from >40 member databases and helps provide insight into the function of these RNAs. This article describes different ways of accessing the data, including searching the website and retrieving the data programmatically over web APIs and a public database. We also demonstrate an example Galaxy workflow for using RNAcentral for RNA-seq differential expression analysis. RNAcentral is available at https://rnacentral.org. © 2020 The Authors. Basic Protocol 1: Viewing RNAcentral sequence reports Basic Protocol 2: Using RNAcentral text search to explore ncRNA sequences Basic Protocol 3: Using RNAcentral sequence search Basic Protocol 4: Using RNAcentral FTP archive Support Protocol 1: Using web APIs for programmatic data access Support Protocol 2: Using public Postgres database to export large datasets Support Protocol 3: Analyze non-coding RNA in RNA-seq datasets using RNAcentral and Galaxy.

LitSumm: large language models for literature summarization of noncoding RNAs
Cited by 10Open Access

Curation of literature in life sciences is a growing challenge. The continued increase in the rate of publication, coupled with the relatively fixed number of curators worldwide, presents a major challenge to developers of biomedical knowledgebases. Very few knowledgebases have resources to scale to the whole relevant literature and all have to prioritize their efforts. In this work, we take a first step to alleviating the lack of curator time in RNA science by generating summaries of literature for noncoding RNAs using large language models (LLMs). We demonstrate that high-quality, factually accurate summaries with accurate references can be automatically generated from the literature using a commercial LLM and a chain of prompts and checks. Manual assessment was carried out for a subset of summaries, with the majority being rated extremely high quality. We apply our tool to a selection of >4600 ncRNAs and make the generated summaries available via the RNAcentral resource. We conclude that automated literature summarization is feasible with the current generation of LLMs, provided that careful prompting and automated checking are applied. Database URL: https://rnacentral.org/.