RiNALMo (Nature Communications 2025)

EVA is a generative foundation model for universal RNA modeling and design, trained on OpenRNA v1 — a curated atlas of 114 million full-length RNA sequences spanning all domains of life.

Generative AI framework for inverse design of 3D RNA structure and function using geometric deep learning, learning design rules from 3D structures to capture complex tertiary interactions (pseudoknots, non-canonical base pairs) with expert-level accuracy for designing functional RNAs including aptamers and ribozymes (bioRxiv 2025)

Unified framework for state-of-the-art pre-trained bio foundation models across genomics and transcriptomics, providing standardized interfaces and pipelines for DNA, RNA, and single-cell models including Evo 2, Geneformer, scGPT, and UCE with streamlined inference, benchmarking, and fine-tuning workflows (213+ stars, 2024-2025)

SQUARNA is a tool for RNA secondary structure prediction. It can take a single RNA sequence or an alignment of sequences as input. SQUARNA handles pseudoknots and can predict alternative structures. SQUARNA allows structural restraints and chemical probing data as additional input and is available at https://github.com/febos/SQUARNA and https://larnal.imol.institute/.

Many full-length RNAs, particularly mRNAs, exceed the ~1K context lengths used to pretrain representative dense RNA encoders, forcing long transcripts to be truncated and preventing their 5′ UTR, CDS, and 3′ UTR from being modeled jointly at single-nucleotide resolution.

MIMIC is a multimodal encoder–decoder foundation model of the central dogma, trained jointly over DNA, RNA, and protein together with a range of structural and functional tracks. A single model embeds any subset of modalities into a shared representation space and generates any modality conditioned…