Linked Life Data

16397064

Source:http://linkedlifedata.com/resource/pubmed/id/16397064

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2006-1-6
pubmed:abstractText
Systemwide functional and structural changes caused by the aging process encourage the implementation of new bioinformatics search strategies for markers of aging. Combinatorial biomarkers should be particularly favored, as they can quantify processes on multiple levels of biological organization and overcome an otherwise limited ability to access heterogeneities in populations. An even more challenging but rational approach is the development of systems biology models to describe molecular pathways and key networks mechanistically as they relate to age. Such reverse engineered models not only indicate critical and diagnostic components (that is, potential biomarkers) but also should be able to predict the progression of aging through computer simulation.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
1539-6150
pubmed:author
pubmed:issnType
Electronic
pubmed:day
4
pubmed:volume
2006
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
pe1
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Biomarkers of aging: combinatorial or systems model?
pubmed:affiliation
School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, PA 19104, USA. andres.kriete@drexel.edu
pubmed:publicationType
Journal Article