All Competitors

Diffusion-based generative RNA model for de novo sequence design, conditioned on function, RNA family, structure, or binding proteins.

Long-context RNA foundation model that predicts splicing, isoform abundance, and variant effects from 64 kb of unspliced pre-mRNA sequence.

OpenAI's frontier reasoning model for life-sciences research, tuned for multi-step workflows in protein engineering, genomics, and drug discovery.

Generative RNA foundation model trained on 114 million full-length sequences for de novo design of tRNAs, aptamers, CRISPR guide RNAs, and mRNAs.

RNA interaction foundation model for conditional, zero-shot design of RNA sequences that bind protein, DNA, or RNA targets without retraining.

RNA foundation model pretrained jointly on sequences and secondary structures for structure prediction, homology and splice site classification.

RNA-RNA interaction prediction framework that scores pairing between long transcripts directly from sequence using Nucleotide Transformer embeddings.

RNA foundation model with 1.6 billion parameters, pretrained on 42 million non-coding RNA sequences for structure prediction and RNA sequence design.