Linked Life Data

19505535

Source:http://linkedlifedata.com/resource/pubmed/id/19505535

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2009-9-25
pubmed:abstractText
In order to understand how a cancer cell is functionally different from a normal cell it is necessary to assess the complex network of pathways involving gene regulation, signaling, and cell metabolism, and the alterations in its dynamics caused by the several different types of mutations leading to malignancy. Since the network is typically complex, with multiple connections between pathways and important feedback loops, it is crucial to represent it in the form of a computational model that can be used for a rigorous analysis. This is the approach of systems biology, made possible by new -omics data generation technologies. The goal of this review is to illustrate this approach and its utility for our understanding of cancer. After a discussion of recent progress using a network-centric approach, three case studies related to diagnostics, therapy, and drug development are presented in detail. They focus on breast cancer, B-cell lymphomas, and colorectal cancer. The discussion is centered on key mathematical and computational tools common to a systems biology approach.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0006-3002
pubmed:author
pubmed:issnType
Print
pubmed:volume
1796
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
129-39
pubmed:dateRevised
2011-3-3
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
A systems biology view of cancer.
pubmed:affiliation
Virginia Bioinformatics Institute, Washington St. (0477), Blacksburg, VA 24061, USA. reinhard@vbi.vt.edu
pubmed:publicationType
Journal Article, Review, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural