From sets to graphs: Towards a realistic enrichment analysis of transcriptomic systems

Bioinformatics

Volumn 27, Issue 13, 2011, Pages

  Geistlinger, Ludwig ^a   Csaba, Gergely ^a   Küffner, Robert ^a   Mulder, Nicola ^b   Zimmer, Ralf ^a  

^a UNIVERSITY OF MUNICH   (Germany)

^b UNIVERSITY OF CAPE TOWN   (South Africa)

Author keywords

[No Author keywords available]

Indexed keywords

PROTEIN;

ALGORITHM; ARTICLE; COMPUTER PROGRAM; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENE REGULATORY NETWORK; GENETICS; HUMAN; METABOLISM; NERVE TUMOR; SIGNAL TRANSDUCTION;

ALGORITHMS; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, NEOPLASTIC; GENE REGULATORY NETWORKS; HUMANS; NEOPLASMS, NERVE TISSUE; PROTEINS; SIGNAL TRANSDUCTION; SOFTWARE;

EID: 79959410946     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btr228     Document Type: Article

References (37)

1. Ashburner, M. et al. (2000) Gene ontology: tool for the unification of biology. Nat. Genet., 25, 25-29.
2. Barry, W.T. et al. (2005) Significance analysis of functional categories in gene expression studies: a structured permutation approach. Bioinformatics, 21, 1943-1949.
3. Breitling, R. et al. (2004) Iterative Group Analysis (iGA): a simple method to enhance sensitivity and facilitate interpretation of microarray experiments. BMC Bioinformatics, 5, 34.
4. Borrello, M.G. et al. (1994) The oncogenic versions of the Ret and Trk tyrosine kinases bind Shc and Grb2 adaptor proteins. Oncogene, 9, 1661-1668.
5. Chaouiya, C. (2007) Petri net modelling of biological networks. Brief. Bioinform., 8, 210-219.
6. Darios, F. and Davletov, B. (2006) Omega-3 and omega-6 fatty acids stimulate cell membrane expansion by acting on syntaxin 3. Nature, 440, 813-817.
7. Dinu, I. et al. (2009) Gene-set analysis and reduction. Brief. Bioinform., 10, 24-34.
8. Eisen, M.B. et al. (1998) Cluster analysis and display of genome-wide expression patterns. Proc. Natl Acad. Sci. USA, 95, 14863-14868.
9. Evangelopoulos, M.E. et al. (2004) Neurotrophin effects on neuroblastoma cells: correlation with trk and p75NTR expression and influence of Trk receptor bodies. J. Neurooncol., 66, 101-110.
10. Faith, J.J. et al. (2008) Many microbe microarrays database: uniformly normalized affymetrix compendia with structured experimental metadata. Nucleic Acids Res., 36, D866-D870.
11. Gama-Castro, S. et al. (2008) Regulon DB (version 6.0): gene regulation model of Escherichia coli K-12 beyond transcription, active (experimental) annotated promoters and Textpresso navigation. Nucleic Acids Res., 36, D120-D124.
12. Gatti, D.M. et al. (2010) Heading down the wrong pathway: on the influence of correlation within gene sets. BMC Genomics, 11, 574.
13. Ge, H. et al. (2001) Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae. Nat. Genet., 29, 482-486.
14. Gentleman, R.C. et al. (2004) Bioconductor: open software development for computational biology and bioinformatics. Genome Biol., 5, 80.
15. Goecks, J. et al. (2010) Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol., 11, 86.
16. Goeman, J.J. and Bühlmann,P. (2007) Analyzing gene expression data in terms of gene sets: methodological issues. Bioinformatics, 23, 980-987.
17. Ihaka, R. and Gentleman, R, (1996) R: a language for data analysis and graphics. J. Comp. Graph. Stat., 5, 299-314.
18. Jansen, R. et al. (2002) Relating whole-genome expression data with protein-protein interactions. Genome Res., 12, 37-46.
19. Keller, A. et al. (2009) A novel algorithm for detecting differentially regulated paths based on gene set enrichment analysis. Bioinformatics, 25, 2787-2794.
20. Khatri, P. and Draghici, S. (2005) Ontological analysis of gene expression data: current tools, limitations, and open problems. Bioinformatics, 21, 3587-3595.
21. Küffner, R. et al. (2000) Pathway analysis in metabolic databases via differential metabolic display (DMD). Bioinformatics, 16, 825-836.
22. Küffner, R. et al. (2010) Petri nets with fuzzy logic (PNFL): reverse engineering and parametrization. PLoS One, 5, 12807.
23. Lee, H.K. et al. (2004) Coexpression analysis of human genes across many microarray data sets. Genome Res., 14, 1085-1094.
24. Liu, M. et al. (2007) Network-based analysis of affected biological processes in Type 2 diabetes models. PLoS Genetics, 3, e96.
25. Meier, R. et al. (2007) The chemokine receptor CXCR4 strongly promotes neuroblastoma primary tumour and metastatic growth, but not invasion. PLoS One, 2, e1016.
26. Miller, F.D. and Kaplan, D.R. (2001) Neurotrophin signalling pathways regulating neuronal apoptosis. Cell. Mol. Life Sci., 58, 1045-1053.
27. Murata, T. (1989) Petri Nets: properties, analysis and applications. Proc. IEEE, 77, 541-580.
28. Ogata, H. et al. (1999) KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res., 27, 29-34.
29. Ohmichi,M. et al. (1991) Nerve growth factor binds to the 140 kd trk protooncogene product and stimulates its association with the src homology domain of phospholipase C gamma 1. Biochem. Biophys. Res. Commun., 179, 217-223.
30. Pan, W. (2002)Acomparative review of statistical methods for discovering differentially expressed genes in replicated microarray experiments. Bioinformatics, 18, 546-554.
31. Schramm, G. et al. (2010) PathWave: discovering patterns of differentially regulated enzymes in metabolic pathways. Bioinformatics, 26, 1225-1231.
32. 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.
33. Ulitsky, I. and Shamir, R. (2007) Identification of functional modules using network topology and high-throughput data. BMC Syst. Biol., 1, 8.
34. Walker, S.R. et al. (2006) Neuroblastoma impairs chemokine-mediated dendritic cell migration in vitro. J. Pediatr. Surg., 41, 260-265.
35. Windhager,L. and Zimmer,R. (2008) Intuitive Modeling of Dynamic Systems with Petri Nets and Fuzzy Logic. German Conference on Bioinformatics, September 9-12, 2008, Dresden, Germany, Vol. 136 of Lecture Notes in Informatics, Gesellschaft für Informatik, Köllen Verlag, Bonn, pp. 106-115.
36. Windhager,L. et al. (2010) Fuzzy modeling. In Koch,I. et al. (eds), Modeling in Systems Biology: The Petri Net Approach, Chapter 9, Springer.
37. Zadeh,L.A. (1963) Fuzzy sets. Inform. Control, 8, 338-353.