Our services

As a solutions provider, we offer consultancy services in addition to our home-grown software. In consultancy mode, we can provide value in various ways, including co-development of entirely new workflows, customization or integration of our existing software to better fit your use-case, as well as joint research for more open ended endeavours. If you are interested in our existing software, check out our platform via the link below or the menubar on top.

Aspect Analytics has strong scientific roots, as evidenced by our scientific publications. The core expertise we bring to the table encompasses bioinformatics, machine learning and mass spectrometry. On top of our scientific prowess, our team provides multiple decades of experience in production-grade software engineering, which grants us the capability to turn your scientific ideas into robust software tools to power your lab.

We outlined a couple of typical projects we can tackle in a service-oriented setup to serve as examples. After these examples, we've described the usual flow of an in-depth collaboration for your information. Please let us know if you are interested in exploring collaborations with us, or if you have any questions.

In this section we describe the main process involved in turning your ideas into reliable software. Depending on the open-endedness of your use-case, not all of the steps enumerated below may be relevant. For example, if you're looking to modify or extend an existing Nexus workflow, we can usually skip right to phase 3.

Very often, our collaborators are looking to develop or prototype a new data analysis pipeline, without having a fully crystallized vision of all the details involved. This is quite common since a lot of data analyses cannot be worked out in advance without getting your hands dirty, i.e., prototyping. The goal of the prototyping phase is to get a better mutual understanding of the requirements, as well as an indication of the results of the envisioned data analysis pipeline.

During this phase, our experts will manually perform the type of analysis that is being considered on provided sample data. This is an iterative process during which all stakeholders' understanding of the problem and its potential solutions evolves. The prototyping phase eventually results in a proof-of-principle, manually performed data analysis, which is primarily intended to determine whether or not the approach is worth pursuing in subsequent phases.

Based on the insights gained during prototyping, all stakeholders should have a sufficiently clear idea of the data analysis and what it involves in a broad sense (data, metadata, algorithms, UI, ...). This provides a solid basis to create software engineering specifications, which include user stories, UI mockups and flowcharts that illustrate the various steps the envisioned solution will entail. Additionally, we will perform a gap analysis to determine how much new developments are necessary, taking Aspect Analytics' existing platform and internal tooling into account. All of this information will help us to create a project plan to reify the envisioned data analysis pipeline into a robust, production-grade solution.

In this phase we will implement the software as agreed based on the requirements and project plan that resulted from phase 2. Usually, the development of data analysis solutions is a highly iterative process during which we insist on involving the end users early and frequently. During development, several prototypes will be made available for beta testing and feedback, both in terms of the quality of results generated by the fledgling tools, as well as the associated UX.

Once the development and initial testing of the solution is finalized, we enter an acceptance phase. In this phase, the draft solution is considered near complete, but should nonetheless be rigorously tested by end users to ensure everything works as expected. During acceptance, all testing is to be performed by end users, i.e., the people that will eventually use the solution. This typically entails using the tool in a production-like context to analyze new data sets that were not available during the development phase. When the acceptance phase ends, the development project is considered finalized.

To ensure business continuity, Aspect Analytics provides continuous support for co-developed tools via opt-in retainer agreements. This support covers training of new users, bug fixes as well as minor evolutions of the solution.

Phase 0: contact us

If you've made it this far, perhaps you have a potential collaboration in mind? Should that be the case, we hope you will contact us using the button below to get started!