All Competitors

Fine-tuned Enformer derivative that predicts discrete, interpretable cis-regulatory element class annotations (enhancer, promoter, insulator) directly from DNA sequence across human cell types.

A reasoning LLM fine-tuned on clinical antimicrobial-susceptibility data augmented with mechanistic rationales, predicting susceptibility with explanations for novel isolate-antibiotic pairs.

Conditions a pretrained DNA sequence embedding on CpG methylation to predict gene regulation across cell types and alleles, generalizing zero-shot to imprinting, X-inactivation, and accessibility.

Specificity Foundation Model that predicts transcription factor-DNA binding specificity from sequence using a physics-derived dual-encoder with symmetric contrastive learning.

Specificity Foundation Model that predicts CRISPR gRNA off-target DNA specificity from sequence using a physics-derived dual-encoder with symmetric contrastive learning.

A 120M-parameter genomic foundation model that learns adaptive DNA token boundaries via H-Net-style dynamic chunking instead of fixed k-mer or byte-pair tokenization.

Self-supervised foundation model that learns reusable representations of cancer genomes from somatic SNVs and copy-number alterations across 33 tumor types.

A zebrafish DNA sequence-to-function model predicting cell-type-specific single-cell expression across 85 cell-type x developmental-timepoint combinations during embryogenesis.

A 700M-parameter DNA language model pretrained on the rice pangenome, built as a reusable foundation model for crop genomics and molecular breeding.

Contrastive promoter-protein pretraining that aligns bacterial promoters with their encoded proteins to learn regulatory genomics representations.

A 4.7B-parameter Mixture-of-Experts genomic foundation model pretrained on ~1.2 trillion nucleotide tokens from human-associated microbial genomes.

A promptable DNA language model that generates multi-kilobase plasmid sequences from human-readable component specifications, post-trained with verifiable rewards.

Multimodal deep-learning framework that detects and localizes DNA lesions directly from native nanopore sequencing, built on the damage-aware LesionBERT foundation model.

A multimodal Q-former that fuses DNA sequence, gene context, protein function, and text into a prefix for a frozen LLM, enabling zero-shot genetic variant interpretation.

A unified bio-language Mixture-of-Experts foundation model spanning DNA, protein sequence and structure, and biological text, applied across eight task families from a single checkpoint.

A permutation-invariant denoising transformer trained on ~2 million bacterial community samples to learn member-level stability scores and predict microbiome composition dynamics zero-shot.

A pretrained DNA language model combining Mamba state-space layers, gated dilated convolutions, and Fourier-based attention to capture multi-scale genomic regulatory patterns.

A family of GPT-2-style causal language models pretrained on 539,000+ microbiome samples, enabling zero- and few-shot transfer across microbiome prediction tasks.

An open autoregressive genomic foundation model (0.5B–8B params) with a 6-mer DNA tokenizer, matching Evo2-7B win rates at far higher throughput.

Generative multimodal foundation model that jointly models DNA, RNA, protein, and cellular context across six biological modalities, with SOTA splicing prediction.

An autoregressive nucleotide-and-text foundation model pretrained on ~416B characters from 2,221 eukaryotic species for natural-language-guided conditional generation of DNA and RNA sequences.

A 1.25B-parameter Mixture-of-Experts genomic foundation model for rice, pretrained on 422 Oryza genomes with a 1 Mbp context window.

Self-supervised generative foundation model jointly trained on 91.7M nucleotide sequences and structured annotations spanning 1.076 trillion bases, achieving SOTA on 23 nucleotide-language benchmarks.

A supervised, chromatin-informed foundation model that predicts regulatory activity directly from plant genomic sequence in Arabidopsis and rice.