4.3 Article

MALDI-typing of infectious algae of the genus Prototheca using SOM portraits

期刊

JOURNAL OF MICROBIOLOGICAL METHODS
卷 88, 期 1, 页码 83-97

出版社

ELSEVIER
DOI: 10.1016/j.mimet.2011.10.013

关键词

MALDI-typing; Mass spectrometry; Peaklist; Prototheca; SOM; Classification

资金

  1. European Funds for Regional Development (EFRE)
  2. State of Saxony (Ministry for Science and the Arts)
  3. Helmholtz Interdisciplinary Graduate School for Environmental Research (HIGRADE)

向作者/读者索取更多资源

Background: MALDI-typing has become a frequently used approach for the identification of microorganisms and recently also of invertebrates. Similarity-comparisons are usually based on single-spectral data. We apply self-organizing maps (SOM) to portray the MS-spectral data with individual resolution and to improve the typing of Prototheca algae by using meta-spectra representing prototypes of groups of similar-behaving single spectra. Results: The MALDI-TOF peaklists of more than 300 algae extracts referring to five Prototheca species were transformed into colored mosaic images serving as molecular portraits of the individual samples. The portraits visualize the algae-specific distribution of high- and low-amplitude peaks in two dimensions. Species-specific pattern of MS intensities were readily discernable in terms of unique single spots of high amplitude MS-peaks which collect characteristic fingerprint spectra. The spot patterns allow the visual identification of groups of samples referring to different species, genotypes or isolates. The use of meta-peaks instead of single-peaks reduces the dimension of the data and leads to an increased discriminating power in downstream analysis. Conclusions: We expect that our SOM portray method improves MS-based classifications and feature selection in upcoming applications of MALDI-typing based species identifications especially of closely related species. (C) 2011 Elsevier B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.3
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据