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Evolving trees for the retrieval of mass spectrometry-based bacteria fingerprints

机译：进化中的树木，用于检索基于质谱的细菌指纹

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In this paper, we investigate the application of Evolving Trees (ET) for the analysis of mass spectrometric data of bacteria. Evolving Trees are extensions of self-organizing maps (SOMs) developed for hierarchical classification systems. Therefore, they are well suited for taxonomic problems such as the identification of bacteria. Here, we focus on three topics, an appropriate pre-processing and encoding of the spectra, an adequate data model by means of a hierarchical Evolving Tree and an interpretable visualization. First, the high dimensionality of the data is reduced by a compact representation. Here, we employ sparse coding, specifically tailored for the processing of mass spectra. In the second step, the topographic information which is expected in the fingerprints is used for advanced tree evaluation and analysis. We adapted the original topographic product for SOMs for ET to achieve a judgment of topography. Additionally we transferred the concept of U-matrix for evaluation of the separability of SOMs to their analog in ET. We demonstrate these extensions for two mass spectrometric data sets of bacteria fingerprints and show their classification and evaluation capabilities in comparison to state of the art techniques.
机译：在本文中，我们研究了进化树（ET）在细菌质谱数据分析中的应用。演化树是为分层分类系统开发的自组织图（SOM）的扩展。因此，它们非常适合分类问题，例如细菌的鉴定。在这里，我们集中于三个主题，适当的光谱预处理和编码，借助层次化的演化树和可解释的可视化的适当数据模型。首先，通过紧凑的表示降低了数据的高维度。在这里，我们采用稀疏编码，专门为质谱处理量身定制。在第二步中，将指纹中预期的地形信息用于高级树评估和分析。我们将原始地形产品用于ET的SOM，以实现对地形的判断。此外，我们将用于评估SOM的可分离性的U-矩阵的概念转移到ET中的类似物上。我们展示了两个扩展的细菌指纹质谱数据集的这些扩展，并展示了它们与现有技术水平相比的分类和评估能力。

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