Linked Life Data

17662553

Source:http://linkedlifedata.com/resource/pubmed/id/17662553

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2007-9-18
pubmed:abstractText
Sequence analysis provides a valuable alternative to phenotypic identification of moulds, especially for isolates lacking characteristic morphology. In this comparative prospective study, isolates that could not be identified by standard phenotypic criteria within 5 days (n = 244) were subjected to sequence analysis and further in-depth phenotypic investigations. Comparison of sequence-based with extended phenotypic identification revealed that sequence analysis was more precise in 52.0% of the isolates; in 38.6% of the isolates, both methods gave concordant results. The construction of a database consisting of high-quality sequences allowed improvement of sequence-based identification. Based on these results, we propose a diagnostic algorithm for the effective use of both phenotypic and genetic procedures for identification of moulds in the diagnostic laboratory.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
0732-8893
pubmed:author
pubmed:issnType
Print
pubmed:volume
59
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
49-60
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Identification of moulds in the diagnostic laboratory--an algorithm implementing molecular and phenotypic methods.
pubmed:affiliation
Institut für Medizinische Mikrobiologie, Universität Zürich, 8006 Zürich, Switzerland. dciardo@immv.unizh.ch
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't