All Competitors

Per-residue classifiers fine-tuned from ESM-2 and ProtT5 that label 20 UniProt protein features and read out what a missense variant disrupts.

CT segmentation foundation model that uses task prompts to segment 83 anatomical structures and lesions across whole-body scans in a single network.

Codon-resolution language model suite pairing a bidirectional encoder with an autoregressive decoder over protein-coding sequences.

RNA foundation language model pretrained on mammalian and viral genomes, fine-tuned to predict translation efficiency, half-life, and splice sites.

Chemical language model that translates IR, UV-Vis and 1H NMR spectra into SMILES structures, replacing the enumerate-and-filter CASE workflow.

Protein-ligand binding affinity prediction for Kd, Ki and IC50 from a pocket structure and a SMILES string, with no docked complex required.

Predicts binding free energy change (ΔΔG) at protein-protein interfaces by scoring bound and unbound states with an inverse folding model.

Multimodal protein model pairing a sequence encoder with a Gene Ontology branch, trained in recursive cycles that clean their own noisy labels.

Mamba-based mature RNA foundation model, contrastively trained on splice isoforms and 400+ mammalian species orthologs for mRNA property prediction.

All-atom protein dynamics simulator that bridges consecutive MD snapshots directly using SO(3)-equivariant two-sided stochastic interpolants.

Masked-autoencoder foundation model for chest radiographs, self-supervised on 1.04 million unlabelled images for disease screening and localization.

Biomolecular structure prediction foundation model covering proteins, small molecules, DNA, RNA, and glycans in a single diffusion framework.

Self-supervised 12-lead ECG encoder that predicts masked patches in latent space, using a cross-lead attention mask shaped by clinical reading.

AAV capsid design platform for gene therapy that steers a peptide language model toward inserts combining receptor targeting and production fitness.

Zero-shot mutation effect scoring for designed and viral proteins, mapping frozen ESM2 representations onto MD and normal-mode dynamic properties.

Generative foundation model for cryo-EM density maps using flow matching, enabling zero-shot denoising, map sharpening, and missing wedge restoration.

Protein language model trained from scratch on MD and normal-mode dynamics, representing residue fluctuation and co-movement from sequence.

Masked-autoencoder foundation model pretrained on digital-stethoscope heart sounds and single-lead ECG for cardiovascular disease detection.

Multimodal LLM aligning natural language, small molecules and proteins in any direction, turning prose design goals into molecules or enzymes.

Protein fitness prediction model meta-trained across ProteinGym deep mutational scans, transferring to unseen assays in context with no task data.

Medical imaging embedding model spanning X-ray, CT, MRI, dermoscopy, OCT, fundus, ultrasound, histopathology and mammography in one encoder.

Sequence-to-function model predicting cell-type- and disease-specific gene expression from DNA, trained on pseudobulk profiles from 22 million cells.

Knowledge-informed cross-species foundation model pre-trained on 101 million human and mouse single-cell transcriptomes to decipher gene regulation.