Design better microbes with a deeper understanding of nature
Let us help you say goodbye to guesswork and unleash the true potential of microbes.
Microbial diversity mapped for machine learning
Coupled with our graph machine learning algorithms, we can derive surprisingly deep insights from all these levels of proprietary data, so as to predict optimal solutions for your strain engineering challenges.
accurate metagenomic sequences of over 50kb on average?
environmental, geological and chemical conditions?
Basecamp Research supercharges your R&D
Feedstock & media optimisation
Discover novel extracellular enzymes, transporters, metabolic enzymes, regulatory proteins, and redox balance systems
Optimise media conditions with real-world environmental metadata
Stress tolerance improvements
Match chaperones, transporters, heat shock proteins, and oxidative stress proteins from extremophiles to your existing strains
Understanding the unknown
Learn how your strain produces your molecule of interest
Overcome regulatory barriers with proteins from closely related species
Locate precisely where to collect more of your desired strain
Identify co-evolved microbes and compatible growth conditions
Learn from novel metabolic branches and pathways from closely related organisms
Expression & regulation
Discover new promoters, ribosomal binding sites, terminators, and transcription factors
See how we can help with your target enzymes and applications
So whether you're a synthetic biologist developing living therapeutics, a metabolic engineer enhancing biofuel production, or an enzymologist designing biocatalysts for bioplastics, give us a shout!
Future-proofed data collection
We're building a robust model for long term biodiversity protection through our global sampling partnerships. Each of our samples is collected in compliance with the Nagoya Protocol and with pre-negotiated permission to commercialise with our industry partners. Our aim is to create a world where industrial innovation protects, supports and revitalises our natural biodiversity.