Biology Reference
In-Depth Information
myocardial infarction: a proof-of-concept investigation.
J Biomed Inform 2010; 43 (5):812 e 9.
14. McDermott JE, Diamond DL, Corley C, et al. Topo-
logical analysis of protein co-abundance networks
identi
29. Azuaje FJ, Rodius S, Zhang L, et al. Information en-
coded in a network of in
ammation proteins predicts
clinical outcome after myocardial infarction. BMC Med
Genomics 2011; 4 :59.
30. Yu H, Kim PM, Sprecher E, et al. The importance of
bottlenecks in protein networks: correlation with gene
essentiality and expression dynamics. PLOS Comput
Biol 2007; 3 (4):e59.
31. Joy MP, Brock A, Ingber DE, et al. High-betweenness
proteins in the yeast protein interaction network.
J Biomed Biotechnol 2005; 2005 (2):96 e 103.
32. Ragusa M, Avola G, Angelica R, et al. Expression
pro
es novel host targets important for HCV infec-
tion and pathogenesis. BMC Syst Biol 2012; 6 (1):28.
15. Bose R, Molina H, Patterson AS, et al. Phosphoproteo-
mic analysis of Her2/neu signaling and inhibition. Proc
Natl Acad Sci USA 2006; 103 (26):9773 e 8.
16. Chen J, Sam L, Huang Y, et al. Protein interaction
network underpins concordant prognosis among
heterogeneous breast cancer signatures. J Biomed Inform
2010; 43 (3):385 e 96.
17. Chen L, Xuan J, Riggins RB, et al. Identifying cancer
biomarkers by network-constrained support vector
machines. BMC Syst Biol 2011; 5 :161.
18. Sanz-Pamplona R, Aragues R, Driouch K, et al.
Expression of endoplasmic reticulum stress proteins is
a candidate marker of brain metastasis in both ErbB-2
c network features of the apoptotic
machinery explain relapse of acute myeloid leukemia
after chemotherapy. BMC Cancer 2010; 10 :377.
33. Hernandez-Toro J, Prieto C. De las Rivas J. APID2NET:
uni
le and speci
ed interactome graphic analyzer. Bioinformatics
2007; 23 (18):2495 e 7.
34. Chavali S, Barrenas F, Kanduri K, et al. Network
properties of human disease genes with pleiotropic
effects. BMC Syst Biol 2010; 4 :78.
35. Aerts S, Lambrechts D, Maity S, et al. Gene prioritiza-
tion through genomic data fusion. Nat Biotechnol 2006;
24 (5):537 e 44.
36. Franke L, vanBakel H, Fokkens L, et al. Reconstruction of
a functional human gene network, with an application
for prioritizing positional candidate genes. Am J Hum
Genet 2006; 78 (6):1011 e 25.
37. Wu X, Jiang R, Zhang MQ, et al. Network-based global
inference of human disease genes. Mol Syst Biol 2008; 4 :
189.
38. Staiger C, Cadot S, Kooter R, et al. A critical evaluation
of network and pathway-based classi
รพ
and ErbB-2- primary breast tumors. Am J Pathol 2011;
179 (2):564 e 79.
19. Dao P,WangK, Collins C, et al. Optimallydiscriminative
subnetwork markers predict response to chemotherapy.
Bioinformatics 2011; 27 (13):i205 e 13.
20. LiuH, Su J, Li J, et al. Prioritizing cancer-relatedgeneswith
aberrant methylation based on a weighted protein e
protein interaction network. BMC Syst Biol 2011; 5 :158.
21. Borro M, Gentile G, De Luca OT, et al. Speci
c effects
exerted by B-lymphoproliferative diseases on peripheral
T-lymphocyte protein expression. Br J Haematol 2010;
150 (4):463 e 72.
22. Tseng CW, Lin CC, Chen CN, et al. Integrative network
analysis reveals active microRNAs and their functions
in gastric cancer. BMC Syst Biol 2011; 5 :99.
23. Wang YC, Chen BS. A network-based biomarker
approach for molecular investigation and diagnosis of
lung cancer. BMC Med Genomics 2011; 4 :2.
24. Chang W, Ma L, Lin L, et al. Identi
ers for outcome
prediction in breast cancer.
PLoS ONE
2012; 7 (4):
e34796.
39. Chuang HY, Lee E, Liu YT, et al. Network-based
classi
cation of breast cancer metastasis. Mol Syst Biol
2007; 3 :140.
40. Lee E, Chuang HY, Kim JW, et al. Inferring pathway
activity toward precise disease classi
cation of novel hub
genes associated with liver metastasis of gastric cancer.
Int J Cancer 2009; 125 (12):2844 e 53.
25. Chavez JD, Hoopmann MR, Weisbrod CR, et al.
Quantitative proteomic and interaction network analysis
of cisplatin resistance in HeLa cells. PLoS ONE 2011; 6 (5):
e19892.
26. Wu Z, Zhao XM, Chen L. A systems biology approach
to identify effective cocktail drugs. BMC Syst Biol 2010;
4 (Suppl. 2):S7.
27. Barrenas F, Chavali S, Holme P, et al. Network prop-
erties of complex human disease genes identi
cation. PLOS
Comput Biol 2008; 4 (11):e1000217.
41. Taylor IW, Linding R, Warde-Farley D, et al. Dynamic
modularity in protein interaction networks predicts
breast cancer outcome. Nat Biotechnol 2009; 27 (2):
199 e 204.
42. Bonetta L. Protein e protein interactions: Interactome
under construction. Nature 2010; 468 (7325):851 e 4.
43. Xenarios I, Rice DW, Salwinski L, et al. DIP: the data-
base of interacting proteins. Nucleic Acids Res 2000;
28 (1):289 e 91.
44. Bader GD, Betel D, Hogue CW. BIND: the Biomolecular
Interaction Network Database. Nucleic Acids Res 2003;
31 (1):248 e 50.
ed
through genome-wide association studies. PLoS ONE
2009; 4 (11):e8090.
28. Goh KI, Cusick ME, Valle D, et al. The human disease
network. Proc Natl Acad Sci USA 2007; 104 (21):8685 e 90.
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