Linked Life Data

20090175

Source:http://linkedlifedata.com/resource/pubmed/id/20090175

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2010-1-21
pubmed:abstractText
The identification of molecular entities involved in human diseases has been a primary focus of post-genomic biomedicine for pursuing the clinical goals of diagnosis and therapeutic treatment. An emerging perspective in systems biology is that the essential biological roles of molecular entities seem to be well correlated with general molecular network properties. Several types of biological complex networks, including protein interaction networks, have a feature of scale-free networks that relates to fractals (multi-scale self-similarity). Using Alzheimer's Disease (AD) as a case study, we constructed an AD-relevant protein interaction subnetwork. We further developed a computational framework based on Ant Colony Optimisation (ACO) to rank disease network relevant nodes. In this framework, the task of ranking nodes is represented as the problem of finding optimal density distributions of 'ant colonies' on all nodes of the network. Our results also revealed fractal-like properties of the network.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1756-0756
pubmed:author
pubmed:issnType
Print
pubmed:volume
2
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
340-52
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Finding fractal patterns in molecular interaction networks: a case study in Alzheimer's disease.
pubmed:affiliation
School of Informatics, Indiana University, Indianapolis, IN 46202, USA. wu@iupui.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S.