All Competitors

Multimodal sequence model spanning proteins, coding DNA, and regulatory DNA for zero-shot fitness scoring and conditional sequence generation.

Prophage island detection in bacterial genomes and metagenome-assembled genomes, pairing a fine-tuned ESM-2 gene classifier with density clustering.

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

Predicts haplotype-specific 3D genome organization and Hi-C contact maps from a single long-read Fiber-seq assay, using no DNA sequence as input.

DNA barcode foundation model whose masked-autoencoder pretraining keeps mask tokens out of the encoder, for arthropod taxonomic classification.

Chromatin signal prediction that fuses reference DNA with per-nucleotide ATAC-seq, calling CTCF and histone marks in any cellular context.

Single-cell DNA methylation foundation model capturing genome-wide CpG dependencies in whole-genome bisulfite sequencing across tissues and species.

Sequence-to-chromatin models for cattle, chicken, pig, and Atlantic salmon that score the regulatory impact of non-coding variants genome-wide.

Genomic foundation model trained on 9.3 trillion DNA base pairs across all domains of life, with 40B parameters and a 1-million-token context.

Functional genomics models predicting RNA-seq, CAGE, and DNase coverage tracks from DNA sequence using striped bidirectional Mamba and attention.

Long-range DNA language model interleaving attention with Mamba2 state-space layers to read 131kb of sequence at single-nucleotide resolution.

Cell-free DNA methylation deconvolution at individual-read resolution, estimating cell-type proportions and condition-specific methylation profiles.

Metagenome misassembly detection and correction that renders read-to-contig alignments as multi-channel images scored by a contrastive CNN.

Long-context generative genomic foundation model with a 98k-nucleotide window, trained on 386 billion bases of eukaryotic DNA for sequence design.

Genomic foundation model for metagenomic annotation: a 500M-parameter bidirectional encoder calling coding regions at single-nucleotide resolution.

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

Yeast gene regulatory network model with one pretrained subnetwork per gene, simulating target-gene response to transcription factor perturbation.

Single-cell ATAC-seq foundation model that builds cell representations from non-zero chromatin peaks via peak-to-gene alignment.

CRISPR-Cas9 repair outcome prediction from microhomology and sequence features, with transfer learning that adapts to a new cell line from 50 samples.

Perturbation representation model embedding CRISPR gene targets and small molecules in one space, transferring genetic screen models to drug response.

4B-parameter generative genome foundation model trained on assembled environmental metagenomes for microbial representation and de novo DNA design.

Autoregressive genomic foundation models from 20M to 1B parameters that solve ten DNA tasks at once and map sequences to text and images.

Plant genomic foundation model with a 64 kb single-nucleotide context that predicts gene structures and generates de novo plant gene sequences.