Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM

Bioinformatics

Volumn 26, Issue 12, 2010, Pages

  Vaske, Charles J ^a   Benz, Stephen C ^b   Sanborn, J Zachary ^b   Earl, Dent ^b   Szeto, Christopher ^b   Zhu, Jingchun ^b   Haussler, David ^a,b   Stuart, Joshua M ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b University of California Santa Cruz   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BREAST TUMOR; COMPUTER PROGRAM; COPY NUMBER VARIATION; FEMALE; GENE EXPRESSION PROFILING; GENETICS; GENOMICS; GLIOBLASTOMA; HUMAN; METHODOLOGY; NEOPLASM;

BREAST NEOPLASMS; DNA COPY NUMBER VARIATIONS; FEMALE; GENE EXPRESSION PROFILING; GENOMICS; GLIOBLASTOMA; HUMANS; NEOPLASMS; SOFTWARE;

EID: 77954195272     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btq182     Document Type: Article

References (46)

1. Alizadeh, A.A. et al. (2000) Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature, 403, 503-511.
2. Allison, D.B. et al. (2006) Microarray data analysis: from disarray to consolidation and consensus. Nat. Rev. Genet., 7, 55-65.
3. Ashburner, M. et al. (2000) Gene ontology: tool for the unification of biology. the gene ontology consortium. Nat. Genet., 25, 25-29.
4. Beer, M.A. and Tavazoie, S. (2004) Predicting gene expression from sequence. Cell, 117, 185-198.
5. BioPAX working group (2004) BioPAX-biological pathways exchange language. Documentation.
6. Chin, S. et al. (2007) High-resolutionACGH and expression profiling identifies a novel genomic subtype of ER negative breast cancer. Genome Biol., 8, R215.
7. Dempster, A.P. et al. (1977) Maximum likelihood from incomplete data via the EM algorithm. J. Roy. Stat. Soc. Series B (Methodol.), 39, 1-38.
8. Dudoit, S. and Fridlyand, J. (2002)Aprediction-based resampling method for estimating the number of clusters in a dataset. Genome Biol., 3, RESEARCH0036.
9. Efroni, S. et al. (2007) Identification of key processes underlying cancer phenotypes using biological pathway analysis. PLoS ONE, 2.
10. Eisen, M.B. et al. (1998) Cluster analysis and display of genome-wide expression patterns. Proc. Natl Acad. Sci. USA, 95, 14863-14868.
11. Friedman, N. and Goldszmidt, M. (1997) Sequential update of bayesian network structure. In Procedings of the 13th Conference on Uncertainty in Artificial Intelligence (UAI'97), Morgan Kaufmann Publishers, pp. 165-174.
12. Friedman, N. (2004) Inferring cellular networks using probabilistic graphical models. Science, 303, 799-805.
13. Gat-Viks, I. and Shamir, R. (2007) Refinement and expansion of signaling pathways: the osmotic response network in yeast. Genome Res., 17, 358-367.
14. Gat-Viks, I. et al. (2005) The factor graph network model for biological systems. RECOMB, Springer, Berlin/Heidelberg, pp. 31-47.
15. Gat-Viks, I. et al. (2006) A probabilistic methodology for integrating knowledge and experiments on biological networks. J. Computat. Biol., 13, 165-181.
16. Golub, T.R. et al. (1999) Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science, 286, 531-537.
17. Joshi-Tope, G. et al. (2005) Reactome: a knowledgebase of biological pathways. Nucleic Acids Res., 33, D428-32.
18. Ju, X. et al. (2007) Akt1 governs breast cancer progression in vivo. Proc. Natl Acad. Sci. USA, 104, 7438-7443.
19. Kerr, M.K. et al. (2000) Analysis of variance for gene expression microarray data. J. Comput. Biol., 7, 819-837.
20. Kschischang, F.R. et al. (2001) Factor graphs and the sum-product algorithm. IEEETIT: IEEE Trans. Inf. Theory, 47, 498-519.
21. Kuan, C.T. et al. (2001) EGF mutant receptorVIII asa molecular target incancer therapy. Endocr. Relat. Cancer, 8, 83-96.
22. Lee, S.-I., (2006) Identifying regulatory mechanisms using individual variation reveals key role for chromatin modification. Proc. Nati Acad. Sci. USA, 103, 14062-14067.
23. Liu, M., et al. (2006) FoxM1B is overexpressed in human glioblastomas and critically regulates the tumorigenicity of glioma cells. Cancer Res., 66, 3593-3602.
24. Mooij, J.M. (2009) libDAI 0.2.3: A free/open source C++ library for Discrete Approximate Inference. Available at http://www.libdai.org/ (last accessed date December 21, 2009).
25. Murphy, K.P. et al. (1999) Loopy belief propagation for approximate inference: an empirical study. In Proceedings of 15th Conference on Uncertainity in Artifical Intelligence, Morgan Kaufmann, pp. 467-475.
26. Naderi, A. et al. (2007) A gene-expression signature to predict survival in breast cancer across independent data sets. Oncogene, 26, 1507-1516.
27. Ogata, H. et al. (1999) Kegg: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res., 27, 29-34.
28. Olshen, A.B. et al. (2004) Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics, 5, 557-572.
29. Pagel, P. et al. (2005) The MIPS mammalian protein-protein interaction database. Bioinformatics, 21, 832-834.
30. Park, J.W. et al. (2008) Unraveling the biologic and clinical complexities of HER2. Clin. Breast Cancer, 8, 392-401.
31. Parsons, D.W. et al. (2008) An integrated genomic analysis of human glioblastoma multiforme. Science, 321, 1807-1812.
32. Sachs, K. et al. (2005) Causal protein-signaling networks derived from multiparameter single-cell data. Science, 308, 523-529.
33. Schaefer, C.F. et al. (2009) PID: the pathway interaction database. Nucleic Acids Res, 37, D674-D679.
34. Segal, E. et al. (2005) From signatures to models: understanding cancer using microarrays. Nat. Genet, 37(Suppl 6) S38-S45.
35. Semenza, G.L. (2000) HIF-1 and human disease: one highly involved factor. Genes Dev, 14, 1983-1991.
36. Storey, J.D. and Tibshirani, R. (2003) Statistical methods for identifying differentially expressed genes in DNA microarrays. Methods Mol. Biol., 224, 149-157.
37. Subramanian, A. et al. (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA, 102, 15545-15550.
38. Tamayo, P. et al. (1999) Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. Proc. Natl Acad. Sci. USA, 96, 2907-2912.
39. Tarca, A.L. et al. (2009)Anovel signaling pathway impact analysis. Bioinformatics, 25, 75-82.
40. TCGA (2008) Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature, 455, 1061-1068.
41. Troyanskaya, O.G. et al. (2002) Nonparametric methods for identifying differentially expressed genes in microarray data. Bioinformatics, 18, 1454-1461.
42. Tusher, V.G. et al. (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl Acad. Sci. USA, 98, 5116-5121.
43. van de Vijver, M.J. et al. (2002) A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med., 347, 1999-2009.
44. Vogel, C. et al. (2001) First-line, single-agent herceptin(r) (trastuzumab) in metastatic breast cancer. a preliminary report. Eur. J. Cancer, 37 (Suppl. 1), 25-29.
45. Wirapati, P. et al. (2008) Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res., 10, R65.
46. Zhu, J. et al. (2009)The UCSC cancer genomics browser. Nat. Methods, 6, 239-240.