All Competitors

RNA-protein contact prediction from sequence, built on ERNIE-RNA and ESM-2 embeddings. Reaches 0.77 auROC where AlphaFold 3 reaches 0.61.

mRNA optimization model that raises codon adaptation, tRNA adaptation, and folding stability at once while preserving the encoded protein sequence.

RNA conformational ensemble generation with a diffusion model, sampling excited states and folding pathways from one structure without MSA input.

De novo protein binder design that recasts structure-predictor confidence as an energy function, replacing ipTM as the hallucination objective.

RNA-binding protein predictor trained on eCLIP data that scores binding intensity along transcripts and recovers motifs via integrated gradients.

Encoder-decoder codon language model that reverse-translates a protein into species-specific coding sequences for synthetic mRNA design.

Generative diffusion model that samples biomolecular conformational ensembles for proteins, RNA, and ligands in hours instead of millisecond-scale MD.

RNA secondary structure prediction that turns phylogenetic compensatory-substitution evidence into attention priors over frozen RiNALMo embeddings.

RNA-seq splice junction detection pairing transcriptome-guided alignment with a fine-tuned DNABERT scorer, reaching a mean F1 of 0.971.

Codon-resolution language models trained on 130 million coding sequences from 20,000 species, learning codon rules for translation and mRNA stability.

Zero-shot RNA design pipeline that ranks variants by genomic language model likelihood combined with inverse-folding structural compatibility.

RNA 3D structure reconstruction from cryo-EM density maps, using a 3D U-Net that predicts 18 atom types and assigns sequence by global alignment.

C/D box snoRNA gene predictor for any eukaryote genome, built on DNABERT and able to separate expressed snoRNAs from their pseudogenes.

DNA and RNA language model with a data-driven 4,096-token unigram vocabulary, matching larger genomic foundation models at 89.2M parameters.

Cell-free RNA language model for liquid biopsy, fusing RNA sequence embeddings with cfRNA abundance across 306 billion pretraining tokens.

Transferable coarse-grained force field for molecular dynamics of proteins, RNA, and lipids, built on the MACE equivariant graph architecture.

RNA inverse folding model that designs nucleotide sequences for a target 3D backbone by running discrete diffusion in hyperbolic space.

Ab initio RNA 3D structure prediction from a single sequence, using a composite-likelihood language model and a denoising end-to-end structure module.

RNA language model that reads full-length transcripts up to 10,000 nucleotides, pairing bidirectional state space layers with multi-head attention.

Protein-conditional RNA design model that generates binding RNA sequences for any target protein, with no post-generation optimization step.

RNA sequence design model that generates protein-binding RNAs from a target structure alone, growing sequences outward from an anchored seed.

Histopathology model predicting gene expression and DNA methylation from H&E slides across 23 cancer types, fusing FFPE and fresh-frozen predictors.

Non-coding RNA language model using masked discrete diffusion to unify sequence generation with representation learning, trained on 30M ncRNAs.