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assix-research/synthetic-dna-human-genome-generative-model
synthetic-dna-human-genome-generative-model is a machine learning model from assix-research. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
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Updated Jan 27, 2026
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From the Hugging Face model README
Trained on a dataset of 1 Million Real Human SNPs (Single Nucleotide Polymorphism), this deep learning model generates high-fidelity synthetic DNA sequences.
This project sits at the intersection of Generative AI and Computational Genomics. By learning the latent statistical manifold of human genetics, this AI creates unique, statistically accurate genomes that do not exist in the real world. These genetic blueprints are critical resources for Bioinformatics benchmarking, Synthetic Biology, and the exploration of Future Humanoid Genomes.
This model is not just a statistical tool; it is a foundational step toward understanding the "Source Code of Life" for artificial entities.
This system utilizes a state-of-the-art Deep Convolutional Variational Autoencoder (Conv1D VAE) to compress and reconstruct the complexity of the human genome.
.txt).This tool generates synthetic data based on statistical patterns found in public genomic datasets (OpenSNP).