About UbSeq
Bioinformatics built around the scientific question
An analysis can be technically correct without being the right analysis.
If methodological choices do not match the scientific question, experimental design or limitations of the data, apparently coherent results can quickly become difficult to interpret.
UbSeq was founded on a simple conviction: a good analysis starts with a clear understanding of the project.
Our story
UbSeq grew out of more than ten years of bioinformatics experience across projects carried out in research institutes, university hospitals and private-sector organisations.
Across these projects, the same reality kept emerging: the challenge was not simply to make the tools work.
It was necessary to understand how the data had been generated. Identify potential biases. Choose the right comparisons. Adapt references, filters and parameters. Connect the results to their biological context.
And sometimes, the most important part was simply recognising what the data could genuinely support — and what they could not justify claiming.
Over time, one principle became clear: the value of a bioinformatics analysis lies not only in the tools used, but in the coherence of the reasoning that connects the scientific question to the results.
UbSeq was created from that experience.
Why UbSeq?
In bioinformatics, the quality of an analysis depends not only on the tools used, but also on the choices that surround them.
Every project has its own context: a scientific question, an experimental design, technical constraints and data with their own limitations.
This is precisely where UbSeq brings value.
The analysis is built around the project itself: understanding the data, identifying critical points, defining a coherent strategy and adjusting methodological choices when needed.
The aim is not to apply a standard procedure, but to produce an analysis in which each step can be understood, justified and connected to the scientific question.
The method adapts to the project — not the other way around.
Let’s discuss your project
Do you have a project, data to analyse or results to clarify? Share your context in a few lines so that we can identify the most appropriate way to approach the analysis together.