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Computomics

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

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.

18/06/2026

"It assumes that gene effects are additive and model environments as discrete categories instead of giving them full environmental covariates. So in reality, things can be much messier. Interactions between genes, interactions between genes and environment is not generally linear. And can involve complex combinations. And that is where machine learning and deep learning come into picture. This gap can be filled by that."

In the first episode of our new “Make Sense of Science” explainer series, a new podcast format for breaking down complex topics in a clear and accessible way, Computomics machine learning scientist Alaukik Saxena explains why genomic prediction in plant breeding is not as simple as it may sound.

Classical statistical models remain highly valuable, but they can reach their limits when biology and environment interact in more complex ways. This is where machine learning and deep learning can help fill the gap.

Listen to the episode to learn more about deep learning for genomic prediction in plant breeding. 🎧 👉 https://www.computomics.com/news-reader/podcast-s7e10.html

16/06/2026

Just out: Germany has made modern plant breeding a national priority. For us at Computomics, this is absolutely encouraging because it confirms a direction we have pursued for years: combining , and to help breeders develop better varieties faster 🌱🧬

The High-Tech Agenda aims to speed up innovation cycles for new plant varieties by one third by 2030. That is exactly where our work sits: turning complex biological and environmental data into actionable breeding decisions.

Climate resilience, food security and sustainable agriculture need more than ambition. They need practical technologies already working in breeding programs today.

This is what we are building.

https://www.computomics.com/news-reader/high-tech-agenda-modern-plant-breeding-becomes-a-national-priority-in-germany.html

11/06/2026

Welcome to the fifth episode of our “Breed, Sow, Grow” series 🌱
This blog post is about how we navigate all the phenotypic, genotypic and environmental data we collected - an extensive and complex dataset we call "big data”. It poses challenges for traditional processing tools. Discover how we bring these pieces together to make sense of the data. The goal is that researchers and breeders can make informed decisions - for example, strategically select plants for crossing.

👉 https://www.computomics.com/news-reader/data-drama-breedings-behind-the-scenes.html�

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02/06/2026

Our champion - Christoph Malisi! 🏆 🚴‍♂️ Christoph racked up the most kilometers in the Computomics team - an impressive 215 km in 20 days. He covers all his everyday trips by bike, and biked even more due to the sunny weather in May ☀️�Congratulations, Christoph! 👏

01/06/2026

CITY CYCLING: From 4 to 24 May, 2026, bikers of Tübingen once again gave it their all! Thousands actively stepped up, saving 114 tons of CO2 in 20 days 🚴🚴‍♂️🚴‍♀️ Fun fact: In the first year of the STADTRADELN competition, Tübingen came out on top against 21 other municipalities and took first place as the "most bicycle-active city”.

Of course the Computomics team joined - to reduce as many CO2-kilometers as possible, to breathe in the morning air on our way to work, and also because it’s fun! ☺️ 🚴‍♂️

27/05/2026

Breeding data is extensive, fragmented, and often hard to interpret. CropCompass brings it together and turns complex data into clear insights 🌱📊

Interpret your genotype, phenotype, and metadata via interactive visualizations that work on top of your existing Breeding Management Software. Make confident decisions more easily - for better crop placement, and for stronger, more resilient varieties.

More 👉 https://www.computomics.com/solutions/climate-smart-breeding/cropcompass.html

26/05/2026

"If I look at a scientific career, it's like a river flowing downstream, and each of us will put a foot in that river and join that flow of scientific discovery." ⛵️🏞️

In this episode of the Computomics podcast, Dr. Rex Bernardo reflects not only on predictive plant breeding and AI, but also on the people who shape science along the way. It is a conversation about new technologies, collaboration, teaching, and helping the next generation find their place in a fast-changing field.

Listen to this thoughtful and inspiring episode 🎧 👉 https://www.computomics.com/news-reader/podcast-s7e9.html

22/05/2026

"For me, I think the most promising trend is to look at AI and machine learning to answer new types of questions, rather than to look into things that are already being done. Through non-machine learning means, or through the traditional statistical techniques, so to speak." 💪🏽🤖

In this episode of the Computomics podcast, Dr. Rex Bernardo shares his perspective on where AI can make the biggest difference in plant breeding. Instead of only improving existing predictions, he points to the bigger opportunity: using machine learning to tackle entirely new questions and support better breeding decisions.

A thoughtful conversation on predictive breeding, new technology, and where the field is heading next 🎧 👉 https://www.computomics.com/news-reader/podcast-s7e9.html

21/05/2026

"When you have a candidate that you have DNA fingerprints on, and you try to predict the performance of that candidate based on other individuals that have the same DNA fingerprints, and you also have evaluated out in the field, the initial focus was to try to use machine learning to predict, yield, predict moisture, predict plant height, predict other traits. So basically, doing the same things that we already do and trying to see if we can do it better. And now we're working into realms of, well, can we actually predict what a breeder would select? Can we do that? And our answer is yes." 🧬🫆🤖

In this episode of the Computomics podcast, Dr. Rex Bernardo discusses the evolution of predictive plant breeding, from early molecular markers to today’s machine learning and AI approaches. He explains how these tools can support not only trait prediction, but also more complex breeding decisions, such as whether a line is likely to be selected or become a successful variety. The conversation also highlights community-focused work on leafy African vegetables in Minnesota. It reflects on how plant breeding education must evolve to prepare future breeders for a more interdisciplinary, data-driven field.

Listen to the conversation on new technologies and not leaving anyone behind 🎧 👉 https://www.computomics.com/news-reader/podcast-s7e9.html

04/05/2026

Computomics' AI-driven platform pairs predictive breeding with pangenome visualization, giving you the architecture behind every crossing decision

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

Webseite

https://computomics.com/

Benachrichtigungen

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