VisHiC - Hierarchical functional enrichment analysis of microarray data

Nucleic Acids Research

Volumn 37, Issue SUPPL. 2, 2009, Pages

  Krushevskaya, Darya ^a   Peterson, Hedi ^a,b   Reimand, Jüri ^a   Kull, Meelis ^a,b   Vilo, Jaak ^a,b  

^a UNIVERSITY OF TARTU   (Estonia)

^b Quretec ^*  (Estonia)

Author keywords

[No Author keywords available]

Indexed keywords

ADENOSINE TRIPHOSPHATE; SERUM RESPONSE FACTOR;

ARTICLE; BINDING SITE; EXTRACELLULAR MATRIX; GENE CLUSTER; GENE EXPRESSION; HEART INFARCTION; HUMAN; HUMAN TISSUE; MATHEMATICAL COMPUTING; MICROARRAY ANALYSIS; MITOCHONDRION; MOLECULAR IMAGING; MUSCLE; PRIORITY JOURNAL; PROTEIN BINDING; WEB BROWSER;

ALGORITHMS; CARDIOVASCULAR DISEASES; CLUSTER ANALYSIS; COMPUTER GRAPHICS; EXTRACELLULAR MATRIX; GENE EXPRESSION PROFILING; HUMANS; MITOCHONDRIA; MYOCARDIUM; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; SOFTWARE;

EID: 67849092444     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gkp435     Document Type: Article

References (37)

1. Brazma,A., Hingamp,P., Quackenbush,J., Sherlock,G., Spellman,P., Stoeckert,C., Aach,J., Ansorge,W., Ball,C.A., Causton,H.C. et al. (2001) Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat. Genet., 29, 365-371.
2. Schena,M., Shalon,D., Davis,R.W. and Brown,P.O. (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science, 270, 467-470.
3. Ross,D.T., Scherf,U., Eisen,M.B., Perou,C.M., Rees,C., Spellman,P., Iyer,V., Jeffrey,S.S., Van de Rijn,M., Waltham,M. et al. (2000) Systematic variation in gene expression patterns in human cancer cell lines. Nat. Genet., 24, 227-235.
4. Ge,X., Yamamoto,S., Tsutsumi,S., Midorikawa,Y., Ihara,S., Wang,S.M. and Aburatani,H. (2005) Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues. Genomics, 86, 127-141.
5. Loh,Y.H., Wu,Q., Chew,J.L., Vega,V.B., Zhang,W., Chen,X., Bourque,G., George,J., Leong,B., Liu,J. et al. (2006) The Oct4 and Nanog transcription network regulates pluripotency in mouse embryonic stem cells. Nat. Genet., 38, 431-440.
6. Hu,Z., Killion,P.J. and Iyer,V.R. (2007) Genetic reconstruction of a functional transcriptional regulatory network. Nat. Genet., 39 683-687.
7. Parkinson,H., Kapushesky,M., Kolesnikov,N., Rustici,G., Shojatalab,M., Abeygunawardena,N., Berube,H., Dylag,M., Emam,I., Farne,A. et al. (2009) ArrayExpress update-from an archive of functional genomics experiments to the atlas of gene expression. Nucleic Acids Res., 37, D868-D872.
8. Barrett,T., Troup,D.B., Wilhite,S.E., Ledoux,P., Rudnev,D., Evangelista,C., Kim,I.F., Soboleva,A., Tomashevsky,M. and Edgar,R. (2007) NCBI GEO: Mining tens of millions of expression profiles-database and tools update. Nucleic Acids Res., 35, D760-D765.
9. Allison,D.B., Cui,X., Page,G.P. and Sabripour,M. (2006) Microarray data analysis: From disarray to consolidation and consensus. Nat. Rev. Genet., 7, 55-65.
10. Troyanskaya,O.G. (2005) Putting microarrays in a context: Integrated analysis of diverse biological data. Brief Bioinformatics, 6 34-43.
11. Eisen,M.B., Spellman,P.T., Brown,P.O. and Botstein,D. (1998) Cluster analysis and display of genome-wide expression patterns. Proc. Natl Acad. Sci. USA, 95, 14863-14868.
12. Tavazoie,S., Hughes,J.D., Campbell,M.J., Cho,R.J. and Church,G.M. (1999) Systematic determination of genetic network architecture. Nat. Genet. 22, 281-285.
13. Ashburner,M., Ball,C.A., Blake,J.A., Botstein,D., Butler,H., Cherry,J.M., Davis,A.P., Dolinski,K., Dwight,S.S., Eppig,J.T. et al. (2000) Gene ontology: Tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet., 25, 25-29.
14. Garge,N.R., Page,G.P., Sprague,A.P., Gorman,B.S. and Allison,D.B. (2005) Reproducible clusters from microarray research: Whither? BMC Bioinformatics, 6(Suppl. 2), S10.
15. Draghici,S., Khatri,P., Martins,R.P., Ostermeier,G.C. and Krawetz,S.A. (2003) Global functional profiling of gene expression. Genomics, 81, 98-104.
16. Reimand,J., Kull,M., Peterson,H., Hansen,J. and Vilo,J. (2007) g:PRofiler-a web-based toolset for functional profiling of gene lists from large-scale experiments. Nucleic Acids Res., 35, 193-200.
17. Huang da,W., Sherman,B.T. and Lempicki,R.A. (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc., 4, 44-57.
18. Kapushesky,M., Kemmeren,P., Culhane,A.C., Durinck,S., Ihmels,J., Krner,C., Kull,M., Torrente,A., Sarkans,U., Vilo,J. and Brazma,A. (2004) Expression Profiler: Next generation-an online platform for analysis of microarray data. Nucleic Acids Res., 32, W465-W470.
19. Segal,E., Yelensky,R., Kaushal,A., Pham,T., Regev,A., Koller,D. and Friedman,N. (2004) GeneXPress: A visualization and statistical analysis tool for gene expression and sequence data. Proceedings of the 11th International Conference on Intelligent Systems for Molecular Biology (ISMB). Glasgow, UK.
20. Chalmel,F. and Primig,M. (2008) The Annotation, Mapping, Expression and Network (AMEN) suite of tools for molecular systems biology. BMC Bioinformatics, 9, 86.
21. Torrente,A., Kapushesky,M. and Brazma,A. (2005) A new algorithm for comparing and visualizing relationships between hierarchical and flat gene expression data clusterings. Bioinformatics, 21, 3993-3999.
22. Adryan,B. and Schuh,R. (2004) Gene-Ontology-based clustering of gene expression data. Bioinformatics, 20, 2851-2852.
23. Okada,Y., Sahara,T., Mitsubayashi,H., Ohgiya,S. and Nagashima,T. (2005) Knowledgeassisted recognition of cluster boundaries in gene expression data. Artif. Intell. Med., 35, 171-183.
24. Seo,J., Gordish-Dressman,H. and Hoffman,E.P. (2006) An interactive power analysis tool for microarray hypothesis testing and generation. Bioinformatics, 22, 808-814.
25. Dotan-Cohen,D., Melkman,A.A. and Kasif,S. (2007) Hierarchical tree snipping: Clustering guided by prior knowledge. Bioinformatics, 23, 3335-3342.
26. Ovaska,K., Laakso,M. and Hautaniemi,S. (2008) Fast Gene Ontology based clustering for microarray experiments. BioData Min., 1, 11.
27. Kull,M. and Vilo,J. (2008) Fast approximate hierarchical clustering using similarity heuristics. BioData Min., 1, 9.
28. Jain,A.K., Murty,M.N. and Flynn,P.J. (1999) Data clustering: A review. ACM Comput. Surv., 31, 264-323.
29. Huang,daW., Sherman,B.T. and Lempicki,R.A. (2009) Bioinformatics enrichment tools: Paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res., 37, 1-13.
30. Vastrik,I., D'Eustachio,P., Schmidt,E., Joshi-Tope,G., Gopinath,G., Croft,D., de Bono,B., Gillespie,M., Jassal,B., Lewis,S. et al. (2007) Reactome: A knowledge base of biologic pathways and processes. Genome Biol., 8, R39.
31. Kanehisa,M., Araki,M., Goto,S., Hattori,M., Hirakawa,M., Itoh,M., Katayama,T., Kawashima,S., Okuda,S., Tokimatsu,T. et al. (2008) KEGG for linking genomes to life and the environment. Nucleic Acids Res., 36, D480-D484.
32. Matys,V., Kel-Margoulis,O.V., Fricke,E., Liebich,I., Land,S., Barre-Dirrie,A., Reuter,I., Chekmenev,D., Krull,M., Hornischer,K. et al. (2006) TRANSFAC and its module TRANSCompel: Transcriptional gene regulation in eukaryotes. Nucleic Acids Res., 34, D108-D110.
33. Griffiths-Jones,S., Grocock,R.J., van Dongen,S., Bateman,A. and Enright,A.J. (2006) miRBase: MicroRNA sequences, targets and gene nomenclature. Nucleic Acids Res., 34, D140-D144.
34. Reimand,J. (2006) Gene ontology mining tool GOSt, MSc thesis, University of Tartu.
35. Hall,J.L., Grindle,S., Han,X., Fermin,D., Park,S., Chen,Y., Bache,R.J., Mariash,A., Guan,Z., Ormaza,S. et al. (2004) Genomic profiling of the human heart before and after mechanical support with a ventricular assist device reveals alterations in vascular signaling networks. Physiol. Genomics, 17, 283-291.
36. Fan,W., Waymire,K.G., Narula,N., Li,P., Rocher,C., Coskun,P.E., Vannan,M.A., Narula,J., Macgregor,G.R. and Wallace,D.C. (2008) A mouse model of mitochondrial disease reveals germline selection against severe mtDNA mutations. Science, 319, 958-962.
37. Azhar,G., Zhang,X., Wang,S., Zhong,Y., Quick,C.M. and Wei,J.Y. (2007) Maintaining serum response factor activity in the older heart equal to that of the young adult is associated with better cardiac response to isoproterenol stress. Basic Res. Cardiol., 102, 233-244.