qubeto | quantifying behaviour

We focus on the experiments

so you can focus on the results

Variation of organisms
qubeto focuses on Drosophila, but we can analyse a range of invertebrate model organisms

Adaptable experiments
We work together with our customers to create the experiments they need

Fast & efficient
qubeto delivers informative behaviour data which accelerates our costumers' developmental cycle

Interdisciplinarity
qubeto combines the expertise of biologists with the knowledge of computer scientists

Hard- & Software
We use a unique set of tools in order to increase the quality, accuracy, and speed of the experiments

Big Data & AI
qubeto offers a range of data analyses incorporating Big Data and Artificial Intelligence

Model organisms

Originally developed to track Drosophila larvae, our setup has the ability to image a wide range of small crawling organisms.

Drosophila
Artemia
C. elegans
Daphnia
red Lake fly
white Lake fly

Do you want to know more? Contact us!

Exemplary use cases

Looking back on a long history of solving problems in the area of insect behaviour we can address a wide range of experimental questions.

Locomotion screening
The basic experiment. Analyse the movement efficiency, bending, and much more

Heat gradient screening
The basic experiment. Only this time in a heated environment, so we can measure the reaction towards heat stress

Food intake screening
The basic experiment. Just in 2 colors, so we can measure the food intake of each larvae

This could be your experiment
You have a different question or demand? Tell us ! We are always looking for new use cases

Now you want to know more! Contact us!

Customers & Partners

Team

qubeto is a start-up which was founded in 2020 in Münster. Our team has worked on computer-vision based analysis of insect behaviour since 2012. Together we create novel imaging hardware and develop state-of-the-art tracking algorithms. Big Data, Machine Learning, and Artificial Intelligence are not only buzz words for us, they are our core tools.

Our team of experienced biologists and computer scientists is eager to solve any arising problem. With our enthusiastic attitude and hands-on approach we focus on the customer needs.

Dr. Dimitri Berh

Dimitri is a passionate programmer and has mastered the application of Computer Vision and Machine Learning algorithms for more than ten years.

Julian Bigge

Julian's expertise in Artificial Intelligence and his passion for designing and implementing neural networks in large software projects makes him a perfect fit.

Dr. Matthias Kiel

Matthias gained his PhD in bioinformatics. With his experience with interdisciplinary teams, he is the perfect translator between computer science and biology.

Marit Praetz

Marit lays the groundwork for our data with her hands-on work in the lab. She performs every experiment precisely and fast, due to her attention to detail and efficiency.

Advisory Board

Prof. Dr. Christian Klämbt

Christian is professor for Neurobiology at the WWU . He gives a boost to the experimental design and all biological relevant topics.

Prof. Dr. Benjamin Risse

Benjamin is professor for Computer Vision and Machine Learning at the WWU and advises the team on questions of technology, development, and applications.

Luis Garcia Rodriguez

Luis is excellent in designing and constructing systems for biological research and supports the team in all hardware related issues.

Luis Garcia Rodriguez

Luis is excellent in designing and constructing systems for biological research and will support the team in hardware related issues.

Our history

The qubeto GmbH emerged from the QuBe project, which is funded by the European Regional Development Fund (ERDF).

The QuBe project was also funded by the Federal Ministry for Economic Affairs and Energy and the European Social Fund as part of the EXIST program.

Contact

qubeto GmbH
Mendelstrasse 11
48149 Münster
GERMANY

Phone: +49 (0) 251 980 1660
E-mail:

The next leap in insect behaviour analysis

The AI solution for testing pesticides, chemicals, and other factors