A protein interaction network associated with asthma

Cited 75 time in webofscience Cited 83 time in scopus
  • Hit : 419
  • Download : 17
Identifying candidate genes related to complex diseases or traits and mapping their relationships require a system-level analysis at a cellular scale. The objective of the present study is to systematically analyze the complex effects of interrelated genes and provide a framework for revealing their relationships in association with a specific disease (asthma in this case). We observed that protein-protein interaction (PPI) networks associated with asthma have a power-law connectivity distribution as many other biological networks have. The hub nodes and skeleton substructure of the result network are consistent with the prior knowledge about asthma pathways, and also suggest unknown candidate target genes associated with asthma, including GNB2L1, BRCA1, CBL, and VAV1. In particular, GNB2L1 appears to play a very important role in the asthma network through frequent interactions with key proteins in cellular signaling. This network-based approach represents an alternative method for analyzing the complex effects of candidate genes associated with complex diseases and suggesting a list of gene drug targets. The full list of genes and the analysis details are available in the following online supplementary materials: http://biosoft.kaist.ac.kr:8080/resources/asthma-Ppi. (C) 2008 Elsevier Ltd. All rights reserved.
Publisher
ACADEMIC PRESS LTD ELSEVIER SCIENCE LTD
Issue Date
2008-06
Language
English
Article Type
Article
Keywords

BRONCHIAL EPITHELIAL-CELLS; GROWTH-FACTOR RECEPTOR; GENE-EXPRESSION; COMMUNITY STRUCTURE; SCAFFOLD PROTEIN; TYROSINE KINASE; ACTIVATION; COMPLEX; CENTRALITY; RESOURCE

Citation

JOURNAL OF THEORETICAL BIOLOGY, v.252, no.4, pp.722 - 731

ISSN
0022-5193
DOI
10.1016/j.jtbi.2008.02.011
URI
http://hdl.handle.net/10203/16917
Appears in Collection
PH-Journal Papers(저널논문)BiS-Journal Papers(저널논문)
Files in This Item
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 75 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0