All Competitors

Spatial transcriptomics foundation model giving gene-, cell- and neighborhood-scale embeddings zero-shot, plus in-silico gene knockout in tissue.

Diffusion super-resolution for H&E whole-slide images, steering denoising with SAM-derived structural anchors and adapted DINOv3 semantic control.

Whole-slide histopathology foundation model that fuses 10x, 20x, and 40x views by attending only between adjacent magnifications.

Predicts nine post-translational modification types across plant proteomes by fusing a protein language model with CNN, BiGRU and PSSM branches.

Hybrid diffusion-and-physics docking model that predicts protein-ligand binding poses and generalizes out-of-distribution for virtual screening.

Protein language model for microbial smORF-encoded small proteins, pairing multi-scale convolutions with transformer layers in a compact encoder.

Protein-ligand binding affinity scoring model for virtual screening that generalizes to novel pockets and ligands under strict train-test splits.

Single-cell foundation model tokenizing expression profiles with a residual-VQ autoencoder to generate new cells of a type from held-out examples.

EEG foundation model that corrects low-frequency bias by reconstructing band-standardized time-frequency targets. State of the art on 24 of 41 tasks.

EEG foundation model coupling spatial and temporal transformer branches through a shared soft mixture-of-experts, adapted by tuning 5.1% of weights.

Enzyme-substrate specificity prediction by end-to-end co-folding, with no predefined binding pocket. AUROC 0.766 on unseen enzymes and substrates.

Physics-guided distillation that transfers 3D molecular dynamics knowledge into SMILES language models, improving MoleculeNet property prediction.

Single-cell foundation model adding a gated cell-level contrastive objective to masked expression pretraining for transferable frozen cell embeddings.

Breast cancer histopathology foundation model distilled from three general-purpose PFMs, over 30x smaller with comparable balanced accuracy and AUC.

Dual-target structure-based drug design that fuses two pocket-conditioned Bayesian flow distributions to generate 3D ligands binding both proteins.

Antibody-specific epitope prediction that replaces sequence-offset rotary attention with backbone local-frame 3D geometry. 0.410 MCC on AsEP.

Genome-scale synthetic lethality prediction for any human gene pair from Gene Ontology annotations, no protein interaction network required.

EEG foundation model pretrained to predict structured latent states rather than masked waveforms, reaching 52.94% frozen macro balanced accuracy.

Signal peptide design framework that generates, filters, and ranks cargo-specific secretion signals using evolution-constrained discrete diffusion.

Genomic foundation model on a Mamba, attention, and mixture-of-experts backbone, with 1M-token context for variant scoring and regulatory DNA design.

EEG foundation model for continuous monitoring, using windowed alternating attention to hold KV-cache memory constant on recordings up to 14 hours.

Cellular foundation models predicting how human cells respond to genetic and pharmacological perturbation, trained on petascale multi-omic data.

Structure-free virtual screening model co-embedding protein residues and small molecules from sequence and 2D chemistry, scoring a compound in 10 ms.