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What are precursors and why are they so important?

Unlocking the full potential of voltammetric data analysis: a novel peak recognition approach for (bio)analytical applications

Unraveling the valuable information hidden within complex data, and making that information understandable to non-experts, is a difficult task many scientists in (bio)analysis are confronted with when turning a scientific technology into a (bio)analytical application. Commonly, an expert in the research field is the only one capable of understanding and interpreting the complex data generated by a scientific device. However, if the complex output of the scientific device can be converted into a read-out comprehendible by non-experts, a major step is made towards the fulfillment of the point-of-need, paving the path for a successful application widely used.

In this work, that can be found here, researchers from the AXES Research Group and the NANOlab Centre of Excellence of the University of Antwerp propose a novel approach in which the domain-specific knowledge is the protagonist, rather than the algorithm itself. The expert’s unique, subject-specific knowledge and insight in the data, is the starting point and the fundament on which the novel approach is build. The approach is developed for interpretation of voltammetric data, however it is envisioned that the scope of the approach can be extended to interpretation of signal data in other research fields. In voltammetry, the expert has generally excellent control over the different signals, i.e. the expert can commonly authenticate the origin and presence of each signal. Therefore, instead of trying to unravel patterns in the data, the individual peaks themselves will be used to extract information from the data. As such, it is assured that all the domain-specific knowledge of the expert is fully exploited, and in extent the risk of a black-box approach becomes non-existent.


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