ausblenden:
Schlagwörter:
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Zusammenfassung:
Ion mobility spectrometry combined with multi-capillary columns (MCC/IMS) is a
well known technology for detecting volatile organic compounds (VOCs). We may
utilize MCC/IMS for scanning human exhaled air, bacterial colonies or cell
lines, for example. Thereby we gain information about the human health status
or infection threats. We may further study the metabolic response of living
cells to external perturbations. The instrument is comparably cheap, robust and
easy to use in every day practice. However, the potential of the MCC/IMS
methodology depends on the successful application of computational approaches
for analyzing the huge amount of emerging data sets. Here, we will review the
state of the art and highlight existing challenges. First, we address methods
for raw data handling, data storage and visualization. Afterwards we will
introduce de-noising, peak picking and other pre-processing approaches. We will
discuss statistical methods for analyzing correlations between peaks and
diseases or medical treatment. Finally, we study up-to-date machine learning
techniques for identifying robust biomarker molecules that allow classifying
patients into healthy and diseased groups. We conclude that MCC/IMS coupled
with sophisticated computational methods has the potential to successfully
address a broad range of biomedical questions. While we can solve most of the
data pre-processing steps satisfactorily, some computational challenges with
statistical learning and model validation remain.
