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Computomics

Name: Computomics
Address: EisenbahnStr. 1, Tübingen, 72072, DE
Telephone: +4970715683995

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Computomics was founded in 2012 so our customers can reap the benefits of our machine learning algorithms.

By applying AI to genetics, phenotype, microbiome, and environmental datasets, we unlock the diversity of biological life. Computomics is a team of world-leading experts in machine learning, plant research and bioinformatics. In over 180 projects, we enabled our customers to make data-driven decisions and thereby accelerate sustainable agricultural development that can feed the world. Our advanced machine learning methods enable rapid understanding of genomic data for plant breeding, agricultural, biotech, and microbiome researchers. Computomics has its headquarters in Tübingen, Germany.

28/10/2026

What if your top performer is sitting in the discard pile? 🌱

Field capacity, time and cost force breeders to discard candidates early, and some of those discards would have been winners. Genomic selection narrows the field, but largely ignores environment and management.

⨉SeedScore® predicts trait performance for untested crosses and environments, delivered in an interactive dashboard instead of spreadsheets. Prioritize lines, decide where to test, and export selection lists.

Your field trials confirm the winners. We show you where to look.�https://www.computomics.com/solutions/xseedscore.html

27/10/2026

At Euroseeds and honestly loving it ☀️ The sun’s out, it feels like summer, and the room is full of opportunities.

Nothing beats actually talking to people face to face. If you’re here, come say hello (table #134)! 🌱

26/10/2026

🌱 Valencia, we’ve arrived!
Last night’s Welcome Evening got Euroseeds 2026 off to a flying start, and now we have three full days of big ideas, great people, and serious seed talk ahead. ☕🌾

Wondering which crosses are actually worth making? Come find us at trade table #134. We bring the predictive breeding, you bring the questions.

👉 https://www.computomics.com/events-reader/euroseeds-2026.html

22/10/2026

"I think a very general mistake a lot of European companies make is that people often assume the other person thinks alike. If you go to another country, the difference is often bigger, and you really have to make an effort to understand how to build the goals in this new environment."

📊 More data. Better environmental models. Faster analysis.

Plant breeding has changed significantly over the past decade, but access to advanced tools and infrastructure is still uneven. ⚠️

In the latest Computomics Podcast episode, Felix Sattler explains how environmental variables such as rainfall, humidity, soil composition, and radiation can improve predictions across locations.

We also discuss why smaller breeding programs may benefit from external data science expertise, how to handle inconsistent datasets, and why breeding goals need to reflect the realities of each environment.

Season 8 starts with: “Can AI Make Plant Breeding More Accessible?”
Listen wherever you get your podcasts.
https://www.computomics.com/news-reader/podcast-s8e1-felix-sattler.html

19/10/2026

Great science deserves great marketing 🧬🌱
We’re looking for a full-time Marketing Manager (Strategy & Ex*****on) on-site in . If you combine strategic thinking and market understanding with creativity and hands-on ex*****on, a great team would love to hear from you! 🥳

👉 https://www.computomics.com/company/career.html

16/10/2026

"I think the model in detail might change, but not the general idea of how to model for this environment. What changes is what kind of goals we go for."

🌱 A promising crop variety can look great in the data and still fail in the real world.

In our new podcast episode, Felix Sattler shares an example from pearl millet 🌾 breeding in Niger: red-grain varieties offered nutritional benefits and were less attractive to birds, but consumers did not like the darker color of the porridge they produced.

It is a simple example of a much bigger point: successful plant breeding depends on more than genetics, AI, and predictive models. 🙌🏼 Local preferences, infrastructure, environmental conditions, and trust matter too.

In Season 8, Episode 1 of the Computomics Podcast, we explore what it takes to make AI-driven breeding useful and accessible across very different environments.

Listen now: “Can AI Make Plant Breeding More Accessible?”
https://www.computomics.com/news-reader/podcast-s8e1-felix-sattler.html

15/10/2026

"We can use basically everything that is available for a certain region. So we can use the rainfall, the humidity, the soil composition, the radiation, the whatever, and we use that in our models to, yeah, really try to grasp the environment and not just use environment itself as a factor, but everything that makes this environment."

We are back from Summer break 🏝️☀️
In the first episode of Season 8 of the Computomics Podcast, we talk with Felix Sattler, our very own Bioinformatics Analyst at Computomics, about AI, environmental data, and plant breeding in challenging environments.

From pearl millet field trials in West Africa to predictive breeding models, Felix shares how breeding has changed over the past decade and why better models alone are not enough.

We discuss:
• breeding for resilience instead of maximum yield
• working with messy data and highly variable environments
• the importance of local knowledge and infrastructure
• how AI could support smaller and regional breeding programs

🎧 Listen to Season 8, Episode 1: “Can AI Make Plant Breeding More Accessible?”
https://www.computomics.com/news-reader/podcast-s8e1-felix-sattler.html

14/10/2026

Great varieties don't come from more data. They come from understanding it 🧑🏻‍💻

brings genotype, phenotype, and trial metadata together and turns them into interactive visualizations that make patterns visible at a glance. Right on top of your existing Breeding Management Software.

Spot top performers faster, compare across environments with ease, and select varieties that thrive where they're planted 🌱

See what to expect 👉 https://lnkd.in/dCd4H76n

13/10/2026

Can machine learning predict how a crop will perform in a field it has never grown in?�

In the Center for Data Innovation's latest "5 Q's," Sebastian Schultheiss, CEO of Computomics, explains how nonlinear ML combines genetics, field trials, and environmental data to speed up plant breeding.

The questions cover:�
🌱 What sets Computomics apart in plant breeding�
📊 Which data feeds its crop-performance predictions�
✔️ How to tell when a prediction is reliable enough to act on�
🔒 How proprietary plant data stays protected�
💡 The biggest misconceptions about ML in breeding

Spoiler: it doesn't replace field trials.

Read the full interview: https://www.computomics.com/news-reader/itif-5-qs.html��

08/10/2026

🧬 Genomic prediction pricing has become a rumor market. The figures traded at breeding conferences can differ a hundredfold, and they say almost nothing about your own program.

The better question: what is it worth to you?

🌱 Price it against your own trialing budget, not someone else's crop.
🌱 Count the entries you could drop before planting, then add the value of reaching market sooner.
🌱 Check your data first. If pulling a few seasons of linked trial records takes a month, start there.

The breeding programs seeing real returns sorted out their data before buying a model (two seasons can be enough), and kept their existing breeding system.

Read the full SeedWorld article 👉 https://www.computomics.com/news-reader/seedworld-what-genomic-prediction-is-worth-to-your-program.html

Adresse

EisenbahnStr. 1
Tübingen
72072

Öffnungszeiten

Montag	09:00 - 18:00
Dienstag	09:00 - 18:00
Mittwoch	09:00 - 18:00
Donnerstag	09:00 - 18:00
Freitag	09:00 - 18:00

Telefon

+4970715683995

Website

https://computomics.com/

Benachrichtigungen

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