Instrument Vendors

We are convinced that an increasing level of integration between hardware and software technologies is important to create an efficient, streamlined workflow for the end users. We are always open to discuss potential technology integrations or joint research opportunities with instrument vendors that share our vision.
Via integration with our software, your customers can get seamless access to all of our platform features.

Technology integration

We believe in an integrated future in which end users can perform complex workflows ranging from sample preparation up to data analysis and reporting in a fully streamlined way. As such, we are always interested in dovetailing our software platform with visionary hardware systems.
Integration

Expand your offering

Fill in potential gaps in your solution. A collaboration enables you to provide your customers with access to best-in-class bioinformatics tools, as well as a full-fledged data management platform.

Empowering the end user

Native integrations between key components simplify workflows for the end user. We are convinced that the sum of complementary hard -and software technologies can be greater than its parts.

Strategic partnership

In case of high complementarity of our technologies and a shared vision on how to move forward, we are open to investigating potential strategic partnerships to strengthen both parties involved.

Joint research with Aspect Analytics

As a KU Leuven University spin-off, Aspect Analytics has strong scientific roots, as evidenced by our scientific publications. We remain active in cutting-edge research, with our core expertise encompassing bioinformatics, machine learning and mass spectrometry.

Bioinformatics

We have broad experience analysing biological data, with a primary focus on mass spectrometry imaging and microscopy data analysis. We are currently actively researching techniques for true multimodal data fusion across various imaging and non-imaging modalities.

Machine Learning

Our machine learning expertise includes deep learning, hyperparameter optimization, building and evaluating predictive models in an unsupervised context, as well as Bayesian inference.

Mass spectrometry

We have a long-standing research history in mass spectrometry imaging, including a recently published review paper together with prof. Caprioli. In addition to MSI, we are increasingly involved in analysis of complex LC-MS data.
Two scientists doing joint research