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Updated: Oct 30, 2025

A Strategy for Sensitive, Large Scale Quantitative Metabolomics
Published on: May 27, 2014
Unlocking the full potential of voltammetric data analysis: A novel peak recognition approach for (bio)analytical
Robin Van Echelpoel1, Mats de Jong1, Devin Daems1
1AXES Research Group, University of Antwerp, Groenenborgerlaan 171, 2020, Antwerp, Belgium; NANOlab Centre of Excellence, University of Antwerp, Groenenborgerlaan 171, 2020, Antwerp, Belgium.
Abstract:
Bridging the gap between complex signal data output and clear interpretation by non-expert end-users is a major challenge many scientists face when converting their scientific technology into a real-life application. Currently, pattern recognition algorithms are the most frequently encountered signal data interpretation algorithms to close this gap, not in the least because of their straight-forward implementation via convenient software packages. Paradoxically, just because their implementation is so straight-forward, it becomes cumbersome to integrate the expert's domain-specific knowledge. In this work, a novel signal data interpretation approach is presented that uses this domain-specific knowledge as its fundament, thereby fully exploiting the unique expertise of the scientist. The new approach applies data preprocessing in an innovative way that transcends its usual purpose and is easy to translate into a software application. Multiple case studies illustrate the straight-forward application of the novel approach. Ultimately, the approach is highly suited for integration in various (bio)analytical applications that require interpretation of signal data.
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