首页> 外文期刊>Bioinformatics >Automatic identification of mixed bacterial species fingerprints in a MALDI-TOF mass-spectrum
【24h】

Automatic identification of mixed bacterial species fingerprints in a MALDI-TOF mass-spectrum

机译:自动识别MALDI-TOF质谱图中的混合细菌物种指纹

获取原文
获取原文并翻译 | 示例
       

摘要

Motivation: Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry has been broadly adopted by routine clinical microbiology laboratories for bacterial species identification. An isolated colony of the targeted microorganism is the single prerequisite. Currently, MS-based microbial identification directly from clinical specimens can not be routinely performed, as it raises two main challenges: (i) the nature of the sample itself may increase the level of technical variability and bring heterogeneity with respect to the reference database and (ii) the possibility of encountering polymicrobial samples that will yield a 'mixed' MS fingerprint. In this article, we introduce a new method to infer the composition of polymicrobial samples on the basis of a single mass spectrum. Our approach relies on a penalized non-negative linear regression framework making use of species-specific prototypes, which can be derived directly from the routine reference database of pure spectra. Results
机译:动机:常规临床微生物实验室已广泛采用基质辅助激光解吸/电离飞行时间质谱法进行细菌种类鉴定。目标微生物的分离菌落是唯一前提。目前,不能直接从临床标本中直接进行基于MS的微生物鉴定,因为它提出了两个主要挑战:(i)样品本身的性质可能会增加技术可变性的水平并带来参考数据库的异质性;以及(ii)遇到会产生“混合” MS指纹的微生物样品的可能性。在本文中,我们介绍了一种基于单个质谱图推断微生物样品组成的新方法。我们的方法依赖于利用特定物种原型的惩罚性非负线性回归框架,该框架可以直接从常规纯光谱参考数据库中获得。结果

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号