Train sequence-to-function prediction models with your mutagenesis data
Visualize your variant library data and examine property relationships
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Predict variant effects and map mutagenesis hotspots
Get sequence embeddings and other inferences from open source and proprietary foundation models
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Design optimized sequence libraries using custom design objectives, including multi-objective criteria
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Create different types of libraries - substitution libraries, combinatorial variant libraries, bespoke sequence libraries, and more
Design first round libraries with state-of-the-art evolutionary models
Explore expected library outcomes
Compare library designs by success probability and cost effectiveness
Visualise predicted protein structure
Similar to natural languages, proteins have a language that can be rearranged and assembled to create different functional proteins.
Evolution has acted over billions of years to produce the vast array of proteins in the natural world today.
Learning from these sequences and other biological datasets, our platform distills the statistical patterns encoding functional and stable proteins into large scale AI models.
These models allow us to map out the protein universe and generate novel, functional proteins.
Harness this power by fine-tuning with your own data to design better proteins, faster.
Similar to natural languages, proteins have a language that can be rearranged and assembled to create different functional proteins.
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