A single multiomic experiment can tell researchers a lot. It can show gene expression, chromatin accessibility and epigenetic marks for the same biological system. Getting those datasets into one place, and using them to decide what to test next, is often slower than the experiment itself. In this Spotlight On, we look at Nurture, a company building software to close that gap. Nurture is working on a practical question: how can researchers learn more from each experiment, and use that to choose the next one?
Why multiomic data slows research down
Each data type in a multiomic experiment adds part of the picture. But the datasets often sit in different places, run through separate pipelines and need different tools to interpret.
For discovery teams, that usually means:
Time spent organising files and moving data between systems.
Repeated handoffs between lab scientists and computational scientists.
Difficulty looking at different data types side by side.
Follow-up questions waiting while new analyses are prepared.
This affects the science, not just the workflow. When every new question needs another round of analysis, researchers have fewer chances to follow up on unexpected results before committing to their next experiment.
From crop biology to research infrastructure
Nurture was founded by Chuck Frazier (CEO) and Savannah Dearden (CTO). Both previously worked at Apeel and Temporal, on understanding and influencing how crops respond to their environment.
At Apeel, their work linked epigenetic patterns to produce shelf life and quality. At Temporal, they worked on epigenetic reprogramming to help crops cope with heat stress. At both companies, they kept hitting the same problem: bringing data, analysis and lab work together took far more time and effort than it should have.
Nurture is the result. The aim is to build the infrastructure the founders needed in their own research.
What sets Nurture apart?
Built by people who run experiments. The founders have moved between biological questions, computational analysis and lab validation themselves. The next experiment is central to how they think about the platform.
A view of the whole research cycle. Tellus deals with the immediate problem of working with complex data. Nurture's wider research programme links that software to epigenome measurement, predictive modelling and experimental remodelling.
Testing cause, not just correlation. Observational data can show links between epigenetic state and biological outcomes. Experiments that deliberately change the system can show which of those changes actually matter. Nurture is developing this approach in yeast and plant systems, with the longer-term goal of building models that help researchers decide which interventions to prioritise.
The platform: Tellus
Tellus is Nurture's first product. It brings data storage, processing, visualisation and collaboration for genomic and multiomic research into one place, giving scientists a more direct route from their data to biological interpretation.
Centralised data management, so datasets stay organised and useful beyond the experiment that produced them.
Connected processing and exploration, with analysis outputs in the same place scientists review results and plan follow-up questions.
Interactive visualisation, so lab scientists can explore their data without writing code for every question.
Multiomic context, with complementary measurements viewed together for a fuller picture of the system.
Sharing by link, so colleagues can open and explore the results behind a discussion.
A recent demonstration using public brain organoid data shows how this works. Researchers can look at gene expression across culture ages, check methylation patterns at a gene of interest, then share that exact view with a colleague. The link keeps the genomic location, tracks and settings, so the colleague can pick up the same question and keep going.
Supporting multiomic research
Nurture is partnering with Frontiers in Systems Biology on a Research Topic focused on linking chromatin state to gene expression through combined epigenomic and transcriptomic data. Tellus will host and visualise research data for the topic, and qualifying manuscripts can receive 25% support towards publication fees.
Why it matters for discovery teams
Labs can now generate multiomic data faster than most teams can interpret it. The limit is often the time between getting a result and acting on it, not the measurement itself.
Tools that let lab scientists explore data directly, and share what they find without another round of analysis, shorten that gap. Nurture's bet is that faster interpretation leads to better choices about the next experiment, and over time, to models that help pick it.
What it means for hiring
Companies building research software for multiomics and epigenomics need leaders who understand both the biology and the product. Those profiles are hard to find, and tools companies, biotech and pharma are all competing for them. Senior roles in this space include:
Heads of computational biology and bioinformatics who can set scientific direction and connect computational and lab teams.
CTOs and product leaders who can turn scientific workflows into software that lab scientists will actually use.
Commercial leaders who can sell research platforms into biotech, pharma and academic groups.
Founders and CEOs taking a platform from beta to a wider market.
What's next for Nurture?
Tellus is currently in beta. Nurture is working to make multiomic research easier to access and share, while building the modelling and experimental parts of its wider platform.
The longer-term plan is a connected research cycle: measure biological state, interpret the results, choose an intervention, then use the next experiment to improve understanding. That will need continued experimental validation, but Tellus already gives researchers a way to bring their data together and ask better questions of it.
You can find out more and request beta access at nurture.bio.
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