Authors: Alyssa Morrow, Michal Jastrzebski, Jake Wintermute
Contributors: Siqi Zhao, Justin Gardin, Lood van Niekerk, Valentin Zulkower, Elise Flynn, Joshua Moller, Porfirio Quintero Cadena, Hao Shen, Dana Merrick, Ankit Gupta, Seth Ritter
Ginkgo Bioworks is excited to announce mDD-0, a generative AI model for designing full-length mRNA sequences. Trained with a large dataset of genomic sequences spanning hundreds of species, mDD-0 learns to generate novel mRNA sequences using discrete diffusion. We created mDD-0 with a unique multimodel architecture, allowing it to jointly learn from different regions of an mRNA sequence, including the coding sequence (CDS) and the 3' and 5' untranslated regions (UTRs), to produce an integrated mRNA model.
This new model makes mRNA easier to engineer. With mDD-0 you can:
Generate diverse mRNA sequences that resemble native genomic mRNA
Fine-tune on payload-specific functional features to improve mRNA stability, protein expression, and translation efficiency.
Experimentally validate your mRNA designs by partnering with Ginkgo to access our data generation platform.
Access to the base mDD-0 model is available through Ginkgo's Model API and you can find additional documentation here. If you're interested in building on mDD-0 with additional training data to enhance the efficacy of your payload of interest, contact us today!
Access, documentation & example usage
Access to the base mDD-0 model is available through Ginkgo's Model API and you can find additional documentation here. If you're interested in building on mDD-0 with additional training data to enhance the delivery of your payload of interest, contact us today!