All Competitors

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.

mRNA foundation model pairing Mamba-2 state-space and attention layers to read full-length transcripts at single-nucleotide resolution.

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

Multi-omics foundation model that folds DNA, RNA, and protein into one codon-level nucleotide representation following the central dogma.

Protein-conditioned RNA sequence and structure co-design, refining flow-matched backbones against Lennard-Jones and folding free-energy terms.

Tertiary structure-based RNA design model that fuses RNA backbone geometry with protein language model features of the bound partner protein.

RNA backbone conformer assignment from low-resolution maps, using Bayesian posteriors over a learned library of 3D suite shape clusters.

Crossmodal diffusion model synthesizing bulk tumor gene expression from H&E whole-slide images, so grading and survival prediction need no RNA assay.

Slide-level pathology foundation model that encodes a whole-slide image of any size into one embedding, supervised by paired sequencing data.

RNA 3D structure generation from sequence and base-pair maps using SE(3) flow matching, with no MSAs or structural templates.

Multi-transformer model that predicts tissue-specific alternative splicing outcomes and generalizes zero-shot to unseen cellular conditions.

RNA language model classifying transcripts as coding or long non-coding, using convolutional sequence encoding to fit whole transcripts in context.

Direct RNA nanopore basecaller that translates raw ionic-current signal into nucleotide sequence using a hybrid Mamba-Transformer backbone.

RNA modification classification from nanopore direct-RNA current, resolving m6A, inosine, pseudouridine, Gm, and m1A at single-base resolution.

Metagenomic foundation model pretrained on 1.5 trillion base pairs of wastewater DNA and RNA for pathogen detection and biosurveillance.

RNA foundation model unifying sequence representation, 3D structure prediction, and de novo design. Ranks first on 11 of 13 BEACON tasks.