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Focus, be tenacious, have fun!

Computomics is a bioinformatics company for the genetic analysis of plants

Please introduce yourself and your startup Computomics to our readers!

I’m Dr. Sebastian Schultheiss, one of the co-founders of Computomics. I studied bioinformatics at University of Tübingen and University of Michigan. For my PhD degree, I researched the application of machine learning techniques to biological data, at the FML of the Max Planck Society and the Max Planck Institute for Developmental Biology.

Computomics is a bioinformatics company for the genetic analysis of plants. By using multi-omics datasets, we unlock the diversity of biological life to enable data-driven decisions and thereby accelerating sustainable agricultural development.

Farming has become detached from our lives: we assume the food we consume is simply available. There is a complex supply chain behind it, and it starts with a breeder. We focus on agricultural biotech and breeding companies. Plant breeders in these companies need 8-16 years to develop a new crop variety and are restricted by the number of field plots they have available for trials.

Our highly accurate predictions integrate soil, climate, and plant genetic information. The increased accuracy and data integration can shave three to six years off the decade-long product development timelines in plant breeding.

How did you get the idea of Computomics?

After my PhD, I wanted to use our machine learning-based tools to support applied research in the life sciences. Besides, I had always wanted to start a business of my own, because I saw during my high school and university years, that you can get a lot done when many people work together towards the same goal.

Why did you decide to start with Computomics?

Together with my PhD advisor and his colleagues, we figured that there is quite a demand for good data analysis and wanted to offer it as a service. Since the advent of next-generation sequencing, the cost for sequencing a human genome has dropped from $3 billion USD in 2000 to $180 USD in 2018. This enormous price drop didn’t happen in the data analysis space in the same way, so we figured that analysis would remain a bottleneck. At the same time a first customer requested such a service, so we took that chance and founded Computomics.

What is the vision behind Computomics?

We founded Computomics so farmers and breeders can reap the benefits of our machine learning algorithms. By applying AI to genetics, yield, soil, and climate datasets, we recommend the best breeding strategies and unlock the diversity of biological life. In over 130 projects, we enabled farmers, breeders, and plant protection companies to make data-driven decisions and thereby accelerate sustainable agricultural development that can feed the world.

How difficult was the start and which challenges you had to overcome?

We did have a supportive founder team and a first client, so the start itself was already mapped out. Difficulties arose from obtaining additional funding and in sales, which is typically the most challenging aspect for startups from universities.

Who is your target audience?

Breeders, life science researchers and bioinformaticians working in seed companies, ag biotech and in food companies.

What is the USP of your startup?

We accelerate breeding and reduce time-to-market for commercial varieties by up to 50%, which is a gain of three to six years by accurately predicting yield (and other phenotypes) per environment and location. We use all available information in a machine learning model. With this model, we can predict the performance of complex traits like yield twice as accurate as standard statistical methods. This increases efficiencies and the genetic gain per cycle. We create genetic reference information for plants, microbes, or animals and characterize microbial communities by their metabolic functions.

Can you describe your typical workday ?

Interact with an extremely smart team, talk to clients from somewhere else in the world where plants are growing right now, and think about a machine learning-based solution for a plant genetics challenge. Every day, I get to broaden my knowledge on the most exciting interface of science currently: genetics and machine learning.

Where do you see yourself and your startup Computomics in five years?

We’ll be a medium-sized company, with about 50 employees, market leaders for independent genomics analysis for crops and environmental microbiomes.

What 3 tips would you give other Start-up founders on the way?

Focus, be tenacious, have fun! It’s much better than a job.

More information you will find here

Thank you Dr. Sebastian Schultheiss for the Interview

Statements of the author and the interviewee do not necessarily represent the editors and the publisher opinion again.

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