Linked Life Data

16081296

Source:http://linkedlifedata.com/resource/pubmed/id/16081296

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2005-11-18
pubmed:abstractText
The flow of information through a cell requires the constant remodeling of cell signaling networks. Thus, spatially and temporally resolved microscopy of signaling components is needed to understand the behavior of normal cells as well as to uncover abnormal behavior leading to human disease. Nanoprobe labeling and transmission electron microscopy of cytoplasmic face-up sheets of cell membrane have been developed as a high-resolution approach to map the interactions of proteins and lipid during cell signaling. Membrane sheets are labeled with 3-15 nm electron-dense probes for receptors, signaling proteins and lipids and micrographs record the distributions of the probes relative to each other and to surface features. Here, we establish computational methods to extract spatial coordinates of probes from micrographs, to analyze and statistically validate the clustering and co-clustering of these probes and to integrate results between experiments in order to establish the relative spatial distributions of single and multiple probes. Our analyses, and the resulting programs for automating data collection and for carrying out statistical and clustering analyses provide toolboxes specialized for the spatiotemporal analysis and modeling of signal transduction pathways.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
0968-4328
pubmed:author
pubmed:issnType
Print
pubmed:volume
37
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
14-34
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Characterizing the topography of membrane receptors and signaling molecules from spatial patterns obtained using nanometer-scale electron-dense probes and electron microscopy.
pubmed:affiliation
Department of Computer Science, University of New Mexico, Albuquerque, NM 87110, USA. jz@cs.unm.edu
pubmed:publicationType
Journal Article, Review, Research Support, N.I.H., Extramural