gtca/alphagenome_pytorch

Foundation models for genomics and transcriptomics pretrained on 3,000+ human genomes and 850+ diverse species, enabling chromatin accessibility prediction, splice site detection, and promoter classification across multiple model scales (InstaDeep, NVIDIA & TUM, Nature Methods 2023)

Deep learning-based variant caller

Evo 2 is a state of the art DNA language model for long context modeling and design. Evo 2 models DNA sequences at single-nucleotide resolution at up to 1 million base pair context length using the StripedHyena 2 architecture, using Savanna.

This repository contains the model presented in D3LM: A Discrete DNA Diffusion Language Model for Bidirectional DNA Understanding and Generation.

Pretrained LDARNet (~110M params) with learnable DNA tokenization (dynamic chunking + BiMamba-2).

The plant DNA large language models (LLMs) contain a series of foundation models based on different model architectures, which are pre-trained on various plant reference genomes. All the models have a comparable model size between 90 MB and 150 MB, BPE tokenizer is used for tokenization and 8000…