All Competitors

Protein-protein interaction predictor that adds contact-guided dual attention and a geometric encoder to frozen protein language model embeddings.

Tissue-specific RNA splicing prediction from pre-mRNA sequence, scoring how variants shift splice-site usage across 18 human tissues.

Automated cryo-EM structure determination that fuses density maps with AlphaFold3 predictions, averaging a TM-score of 0.93 on high-resolution maps.

Allosteric binding site prediction from protein sequence alone, using LoRA-tuned protein language models conditioned on the orthosteric pocket.

All-atom biomolecular structure prediction with adapters for allosteric states, user-defined interface constraints, and binding affinity.

Single-cell perturbation-response model that predicts transcriptomic and imaging outcomes of unseen genetic perturbations via a VAE with attention.

Family of CNN foundation models pretrained on multimodal radiology images, a domain-specific alternative to ImageNet transfer learning weights.

Backmapping model that rebuilds all-atom protein and nucleic acid structures from coarse-grained beads and inpaints unresolved residues.

Multimodal foundation model for cardiac biosignals, pretrained by masked modeling on ECG, PPG, and clinical text from ~1.7 million individuals.

Biomedical vision-language assistant for medical visual question answering, pairing Phi-2 with a vision encoder in a 4.2B-parameter model.

Proteomics foundation model for peptide-spectrum scoring and open de novo sequencing, reading over 1,300 modifications from tandem mass spectra.

Self-supervised medical imaging foundation model pretrained on 3.3 million CT, X-ray, ultrasound, pathology, OCT, fundus, and dermoscopy images.

Histopathology image synthesis from a latent diffusion model conditioned jointly on unpaired diagnostic text reports and cell-type masks.

Apple's foundation model trained on behavioral signals from wearables, modeling 27 HealthKit metrics to improve predictions across 57 health tasks.

EEG foundation model with cross-scale spatiotemporal tokenization and sparse structured attention, evaluated on 11 decoding tasks across 16 datasets.

De novo protein backbone design conditioned on a target per-residue flexibility profile, with SE(3)-equivariant flow matching and MD validation.

T-cell receptor specificity prediction that separates general antigens from autoimmune-related ones using ESM-2 embeddings and a topology-aware graph.

DNA foundation model that predicts thousands of functional genomic tracks, from expression and splicing to chromatin, at single base-pair resolution.

Virtual cell transformer that predicts how cells respond to genetic, chemical, or signaling perturbations, generalizing to unseen cellular contexts.

Conditional GAN generating HLA class I pseudo-sequences from a peptide, then resolving them to candidate alleles by nearest-neighbor lookup.

Hierarchical immune cell type annotation for scRNA-seq, rendering expression as images for a CNN. 93.2% mean subtype accuracy over seven datasets.

Plasmid characterization and retrieval model aligning DNA sequences with property text across ten facets, from antimicrobial resistance to host range.

Generative codon language model for mRNA design, trained on 338,417 coding sequences with inference-time masking that preserves the encoded protein.