Finding consistent disease subnetworks across microarray datasets

BMC Bioinformatics

Volumn 12, Issue SUPPL. 13, 2011, Pages

  Soh, Donny ^a,b,c   Dong, Difeng ^a   Guo, Yike ^b   Wong, Limsoon ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b IMPERIAL COLLEGE LONDON   (United Kingdom)

^c INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL LITERATURES; DESCRIPTIVE ANALYSIS; DESCRIPTIVE INFORMATION; INDEPENDENT SET; LUNG CANCER; MICROARRAY ANALYSIS; MICROARRAY DATA; MICROARRAY DATA SETS; REPRODUCIBILITIES; SUBNETWORKS;

DATA PROCESSING; GENES;

DATA REDUCTION;

ACUTE LYMPHOBLASTIC LEUKEMIA; ALGORITHM; ARTICLE; DNA MICROARRAY; DUCHENNE MUSCULAR DYSTROPHY; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORK; GENETICS; HUMAN; LUNG TUMOR; METHODOLOGY; REPRODUCIBILITY;

ALGORITHMS; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORKS; HUMANS; LUNG NEOPLASMS; MUSCULAR DYSTROPHY, DUCHENNE; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PRECURSOR CELL LYMPHOBLASTIC LEUKEMIA-LYMPHOMA; REPRODUCIBILITY OF RESULTS;

EID: 84857863460     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-12-S13-S15     Document Type: Article

References (42)

1. Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A 2001, 98(9):5116-5121. 10.1073/pnas.091062498, 33173, 11309499., http://dx.doi.org/10.1073/pnas.091062498
2. Friedman N, Linial M, Nachman I, Pe'er D. Using Bayesian networks to analyze expression data. J Comput Biol 2000, 7(3-4):601-620. 10.1089/106652700750050961, 11108481., http://dx.doi.org/10.1089/106652700750050961
3. Lähdesmäki H, Hautaniemi S, Shmulevich I, Yli-Harja O. Relationships between probabilistic Boolean networks and dynamic Bayesian networks as models of gene regulatory networks. Signal Process 2006, 86(4):814-834.
4. Khatri P, Draghici S. Ontological analysis of gene expression data: current tools, limitations, and open problems. Bioinformatics 2005, 21(18):3587-3595. 10.1093/bioinformatics/bti565, 2435250, 15994189., http://bioinformatics.oxfordjournals.org/cgi/content/abstract/21/18/3587
5. Goeman JJ, van de Geer SA, de Kort F, van Houwelingen HC. A global test for groups of genes: testing association with a clinical outcome. Bioinformatics 2004, 20:93-99. 10.1093/bioinformatics/btg382, 14693814., http://bioinformatics.oxfordjournals.org/cgi/content/abstract/20/1/93
6. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences of the United States of America 2005, 102(43):15545-15550. 10.1073/pnas.0506580102, 1239896, 16199517., http://www.pnas.org/content/102/43/15545.abstract
7. Sivachenko AY, Yuryev A, Daraselia N, Mazo I. Molecular Networks in microarray Analysis. J. Bioinformatics and Computational Biology 2007, 5(2b):429-456.
8. Pavlidis P, Qin J, Arango V, Mann JJ, Sibille E. Using the Gene Ontology for Microarray Data Mining: A Comparison of Methods and Application to Age Effects in Human Prefrontal Cortex. Neurochemical Research 2004, 29(6):1213-1222., http://dx.doi.org/10.1023/B:NERE.0000023608.29741.45
9. Ein-Dor L, Kela I, Getz G, Givol D, Domany E. Outcome signature genes in breast cancer: is there a unique set?. Bioinformatics 2005, 21(2):171-178. 10.1093/bioinformatics/bth469, 15308542., http://bioinformatics.oxfordjournals.org/cgi/content/abstract/21/2/171
10. Michiels S, Koscielny S, Hill C. Prediction of cancer outcome with microarrays: a multiple random validation strategy. The Lancet 2005, 365(9458):488-492., http://dx.doi.org/10.1016/S0140-6736(05)17866-0
11. Zhang M, Zhang L, Zou J, Yao C, Xiao H, Liu Q, Wang J, Wang D, Wang C, Guo Z. Evaluating reproducibility of differential expression discoveries in microarray studies by considering correlated molecular changes. Bioinformatics 2009, 25(13):1662-1668. 10.1093/bioinformatics/btp295, 2940240, 19417058., http://bioinformatics.oxfordjournals.org/cgi/content/abstract/25/13/1662
12. Lapointe J, Li C, Higgins JP, van de Rijn M, Bair E, Montgomery K, Ferrari M, Egevad L, Rayford W, Bergerheim U, Ekman P, DeMarzo AM, Tibshirani R, Botstein D, Brown PO, Brooks JD, Pollack JR. Gene expression profiling identifies clinically relevant subtypes of prostate cancer. Proceedings of the National Academy of Sciences of the United States of America 2004, 101(3):811-816. 10.1073/pnas.0304146101, 321763, 14711987., http://www.pnas.org/content/101/3/811.abstract
13. Singh D, Febbo PG, Ross K, Jackson DG, Manola J, Ladd C, Tamayo P, Renshaw AA, D'Amico AV, Richie JP, Lander ES, Loda M, Kantoff PW, Golub TR, Sellers WR. Gene expression correlates of clinical prostate cancer behavior. Cancer Cell 2002, 1:203-9. 10.1016/S1535-6108(02)00030-2, 12086878., http://www.ncbi.nlm.nih.gov/pubmed/12086878
14. Garber ME, Troyanskaya OG, Schluens K, Petersen S, Thaesler Z, Pacyna-Gengelbach M, van de Rijn M, Rosen GD, Perou CM, Whyte RI, Altman RB, Brown PO, Botstein D, Petersen I. Diversity of gene expression in adenocarcinoma of the lung. Proceedings of the National Academy of Sciences of the United States of America 2001, 98(24):13784-13789. 10.1073/pnas.241500798, 61119, 11707590., http://www.pnas.org/content/98/24/13784.abstract
15. Bhattacharjee A, Richards WG, Staunton J, Li C, Monti S, Vasa P, Ladd C, Beheshti J, Bueno R, Gillette M, Loda M, Weber G, Mark EJ, Lander ES, Wong W, Johnson BE, Golub TR, Sugarbaker DJ, Meyerson M. Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proceedings of the National Academy of Sciences of the United States of America 2001, 98(24):13790-13795. 10.1073/pnas.191502998, 61120, 11707567., http://www.pnas.org/content/98/24/13790.abstract
16. Pescatori M, Broccolini A, Minetti C, Bertini E, Bruno C, D'amico A, Bernardini C, Mirabella M, Silvestri G, Giglio V, Modoni A, Pedemonte M, Tasca G, Galluzzi G, Mercuri E, Tonali PA, Ricci E. Gene expression profiling in the early phases of DMD: a constant molecular signature characterizes DMD muscle from early postnatal life throughout disease progression. FASEB J 2007, 21(4):1210-1226. 10.1096/fj.06-7285com, 17264171., http://www.fasebj.org/cgi/content/abstract/21/4/1210
17. Haslett JN, Sanoudou D, Kho AT, Bennett RR, Greenberg SA, Kohane IS, Beggs AH, Kunkel LM. Gene expression comparison of biopsies from Duchenne muscular dystrophy (DMD) and normal skeletal muscle. Proceedings of the National Academy of Sciences of the United States of America 2002, 99(23):15000-15005. 10.1073/pnas.192571199, 137534, 12415109., http://www.pnas.org/content/99/23/15000.abstract
18. Soh D, Dong D, Guo Y, Wong L. Enabling more sophisticated gene expression analysis for understanding diseases and optimizing treatments. ACM SIGKDD Explorations 2007, 9:3-14.
19. Dong D, Cui CY, Mow B, Wong L. Deciphering Drug Action and Escape Pathways: An Example on Nasopharyngeal Carcinoma. BICoB '09: Proceedings of the 1st International Conference on Bioinformatics and Computational Biology 2009, 199-210. Berlin, Heidelberg: Springer-Verlag.
20. Cormen TH, Leiserson CE, Rivest RL, Stein C. Introduction to Algorithms. 2001, MIT Press and McGraw-Hill.
21. Ingenuity Systems. 1998, , http://www.ingenuity.com/
22. Kotecha N, Bruck K, Lu W, Shah N. Pathway knowledge base: An integrated pathway resource using BioPAX. Appl. Ontol 2008, 3(4):235-245.
23. Salomonis N, Hanspers K, Zambon AC, Vranizan K, Lawlor SC, Dahlquist KD, Doniger SW, Stuart J, Conklin BR, Pico AR. GenMAPP 2: new features and resources for pathway analysis. BMC bioinformatics 2007, 8:217+. 10.1186/1471-2105-8-217, 1924866, 17588266., http://dx.doi.org/10.1186/1471-2105-8-217
24. Green ML, Karp PD. The outcomes of pathway database computations depend on pathway ontology. Nucl. Acids Res 2006, 34(13):3687-3697. 10.1093/nar/gkl438, 1540720, 16893953., http://nar.oxfordjournals.org/cgi/content/abstract/34/13/3687
25. Soh D, Dong D, Guo Y, Wong L. Consistency, Comprehensiveness and Compatibility of Pathway Databases. BMC Bioinformatics 2010, 11:449. 10.1186/1471-2105-11-449, 2944280, 20819233.
26. Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML, Downing JR, Caligiuri MA, Bloomfield CD, Lander ES. Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring. Science 1999, 286(5439):531-537. 10.1126/science.286.5439.531, 10521349., http://dx.doi.org/10.1126/science.286.5439.531
27. Armstrong SA, Staunton JE, Silverman LB, Pieters R, den Boer ML, Minden MD, Sallan SE, Lander ES, Golub TR, Korsmeyer SJ. MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia. Nature Genetics 2002, 30:41-7. 10.1038/ng765, 11731795., http://www.ncbi.nlm.nih.gov/pubmed/11731795
28. Ross ME, Mahfouz R, Onciu M, Liu HC, Zhou X, Song G, Shurtleff SA, Pounds S, Cheng C, Ma J, Ribeiro RC, Rubnitz JE, Girtman K, Williams WK, Raimondi SC, Liang DC, Shih LY, Pui CH, Downing JR. Gene expression profiling of pediatric acute myelogenous leukemia. Blood 2004, 104(12):3679-3687. 10.1182/blood-2004-03-1154, 15226186., http://dx.doi.org/10.1182/blood-2004-03-1154
29. Yeoh E, ME R, SA S, WK W, D P, R M, FG B, SC R, MV R, A P, C C, D C, D W, X Z, J L, H L, CH P, WE E, C N, L W, JR D. Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. Cancer Cell 2002, 1(2):133-143. 10.1016/S1535-6108(02)00032-6, 12086872.
30. Krishna D, LeDoux J. Murine leukemia virus particles activate Rac1 in HeLa cells. Biochem Biophys Res Commun 2006, 345(3):1184-93. 10.1016/j.bbrc.2006.05.027, 16716260.
31. Wang J, Rao Q, Wang M, Wei H, Xing H, Liu H, Wang Y, Tang K, Peng L, Tian Z, Wang J. Overexpression of Rac1 in leukemia patients and its role in leukemia cell migration and growth. Biochem Biophys Res Commun 2009, 386(4):769-74. 10.1016/j.bbrc.2009.06.125, 19563775.
32. Booden MA, Siderovski DP, Channing JD. Leukemia-associated Rho guanine nucleotide exchange factor promotes G alpha q-coupled activation of RhoA. Molecular and cellular biology 2002, 22(12):4053-61. 10.1128/MCB.22.12.4053-4061.2002, 133844, 12024019.
33. Kristelly R, Gao G, Tesmer JJG. Structural Determinants of RhoA Binding and Nucleotide Exchange in Leukemia-associated Rho Guanine-Nucleotide Exchange Factor. The Journal of Biological Chemistry 2004, 279:47352-47362. 10.1074/jbc.M406056200, 15331592.
34. Katzav S. Flesh and blood: the story of Vav1, a gene that signals in hematopoietic cells but can be transforming in human malignancies. Cancer Lett 2007, 255(2):241-54. 10.1016/j.canlet.2007.04.015, 17590270.
35. Juliana L, Andrew Y, Jr FSA, Bing Y, de los Santos K, Goff SP. Interaction of Moloney murine leukemia virus matrix protein with IQGAP. The EMBO Journal 2006, 25:2155- 2166. 10.1038/sj.emboj.7601097, 1462987, 16628219.
36. Balagopal P, Olney R, Darmaun D, Mougey E, Dokler M, Sieck G, Hammond D. Oxandrolone enhances skeletal muscle myosin synthesis and alters global gene expression profile in Duchenne muscular dystrophy. Am J Physiol Endocrinol Metab 2006, 290(3):E530-9.
37. Baker P, Kearney J, Gong B, Merriam A, Kuhn D, Porter J, Rafael-Fortney J. Analysis of gene expression differences between utrophin/dystrophin-deficient vs mdx skeletal muscles reveals a specific upregulation of slow muscle genes in limb muscles. Neurogenetics 2006, 7(2):81-91. 10.1007/s10048-006-0031-7, 16525850.
38. Garvey S, Rajan C, Lerner A, Frankel W, Cox G. The muscular dystrophy with myositis (mdm) mouse mutation disrupts a skeletal muscle-specific domain of titin. Genomics 2002, 79(2):146-9. 10.1006/geno.2002.6685, 11829483.
39. Hackman P, Vihola A, Haravuori H, Marchand S, Sarparanta J, Seze JD, Labeit S, Witt C, Peltonen L, Richard I, Udd B. Tibial muscular dystrophy is a titinopathy caused by mutations in TTN, the gene encoding the giant skeletal-muscle protein titin. American Journal of Human Genetics 2002, Sep 71(3):492-500.
40. Itoh-Satoh M, Hayashi T, Nishi H, Koga Y, Arimura T, Koyanagi T, Takahashi M, Hohda S, Ueda K, Nouchi T, Hiroe M, Marumo F, Imaizumi T, Yasunami M, Kimura A. Titin mutations as the molecular basis for dilated cardiomyopathy. Biochem Biophys Res Commun 2002, 291(2):385-93. 10.1006/bbrc.2002.6448, 11846417.
41. Gerull B, Gramlich M, Atherton J, McNabb M, K KT, Sasse-Klaassen S, Seidman J, Seidman C, Granzier H, Labeit S, Frenneaux M, Thierfelder L. Mutations of TTN, encoding the giant muscle filament titin, cause familial dilated cardiomyopathy. Nat Genet 2002, 30(2):201-4. 10.1038/ng815, 11788824.
42. Liu M, Liberzon A, Kong SW, Lai WR, Park PJ, Kohane IS, Kasif S. Network-Based Analysis of Affected Biological Processes in Type 2 Diabetes Models. PLoS Genet 2007, 3(6):e96+. 1904360, 17571924.