The present work integrates network analysis with chromatography and proposes a novel analytical procedure to classify the bacterial cell wall collection. The network analysis model can capture the heterogeneity present in the datasets and hence can provide unsupervised classification. The proposed approach is successfully applied for classifying the peptidoglycan samples of certain bacterial collections belonging to the class of Alphaproteobacteria. The obtained classification results are found to correlate well with their relative similarity in the peptidoglycan compositions. In summary, the proposed network analysis approach can be helpful in automatizing the bacterial cell wall analysis. The proposed approach can be useful to accelerate the research related to understanding the morphology of bacterial cell walls, host–pathogen interaction and development of effective antibiotics.

中文翻译：

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将网络分析与色谱法整合：引入基于化学计量学-色谱法的新型分析程序来对细菌细胞壁收集进行分类

本工作将网络分析与色谱相结合，并提出了一种新颖的分析程序来对细菌细胞壁收集进行分类。网络分析模型可以捕获数据集中存在的异质性，因此可以提供无监督的分类。所提出的方法已成功地用于对属于Alphaproteobacteria类别的某些细菌集合的肽聚糖样品进行分类。发现获得的分类结果与其在肽聚糖组合物中的相对相似性良好相关。总而言之，所提出的网络分析方法可有助于细菌细胞壁分析的自动化。所提出的方法可能有助于加速与了解细菌细胞壁形态有关的研究，