Linked Life Data

18007678

Source:http://linkedlifedata.com/resource/pubmed/id/18007678

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
2007-11-16
pubmed:abstractText
The treatment of bacterial infections is increasingly complicated because microorganisms can develop resistance to antimicrobial agents. This article discusses the information that is required to predict when antibiotic resistance is likely to emerge in a bacterial population. Indeed, the development of the conceptual and methodological tools required for this type of prediction represents an important goal for microbiological research. To this end, we propose the establishment of methodological guidelines that will allow researchers to predict the emergence of resistance to a new antibiotic before its clinical introduction.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
1740-1534
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
5
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
958-65
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Predicting antibiotic resistance.
pubmed:affiliation
Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública and Unidad Asociada al CSIC Resistencia a los Antibióticos y Virulencia Bacteriana, Cantoblanco, 28049-Madrid, Spain. jlmtnez@cnb.uam.es
pubmed:publicationType
Journal Article, Review, Research Support, Non-U.S. Gov't