|
|||||
|
|
Identification and Discrimination of Oral Asaccharolytic Eubacterium spp. by Pyrolysis Mass Spectrometry and Artificial Neural Networks |
|
| Authors: | Royston Goodacre Sarah J Hiom Sarah L Cheeseman David Murdoch Andrew J Weightman William G Wade |
| Institution: | (1) Institute of Biological Sciences, University of Wales, Aberystwyth, Dyfed, SY23 3DA, UK , GB;(2) Department of Oral and Dental Science, University of Bristol, Lower Maudlin Street, Bristol, BS1 2LY, UK , GB;(3) Department of Medical Microbiology, Bristol Royal Infirmary, Bristol, BS2 8HW, UK , GB;(4) School of Pure and Applied Biology, University of Wales College of Cardiff, PO Box 915, Cardiff, CF1 3TL, UK , GB |
| Abstract: | Curie-point pyrolysis mass spectra were obtained from 29 oral asaccharolytic Eubacterium strains and 6 abscess isolates previously identified as Peptostreptococcus heliotrinreducens. Pyrolysis mass spectrometry (PyMS) with cluster analysis was able to clarify the taxonomic position of this group of organisms. Artificial neural networks (ANNs) were then trained by supervised learning (with the back-propagation algorithm) to recognize the strains from their pyrolysis mass spectra; all Eubacterium strains were correctly identified, and the abscess isolates were identified as un-named Eubacterium taxon C2 and were distinct from the type strain of P. heliotrinreducens. These results demonstrate that the combination of PyMS and ANNs provides a rapid and accurate identification technique. |
| Keywords: | |
| 本文献已被 SpringerLink 等数据库收录！ | |