Enhancing biological relevance of a weighted gene co-expression network for functional module identification

Journal of Bioinformatics and Computational Biology

Volumn 9, Issue 1, 2011, Pages 111-129

  Prom On, Santitham ^a   Chanthaphan, Atthawut ^a   Chan, Jonathan Hoyin ^a   Meechai, Asawin ^a  

^a KING MONGKUT'S UNIVERSITY OF TECHNOLOGY THONBURI   (Thailand)

Author keywords

Biological relevance; functional module; Weighted Gene Co Expression Network

Indexed keywords

ALGORITHM; ARTICLE; AUTISM; BIOLOGICAL MODEL; BIOLOGY; CHILD; COLORECTAL TUMOR; COMPARATIVE STUDY; COMPUTER PROGRAM; COMPUTER SIMULATION; DNA MICROARRAY; EVALUATION; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORK; GENETIC DATABASE; GENETICS; HUMAN; STATISTICS; VALIDATION STUDY;

ALGORITHMS; CHILD; CHILD DEVELOPMENT DISORDERS, PERVASIVE; COLORECTAL NEOPLASMS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DATABASES, GENETIC; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORKS; HUMANS; MODELS, GENETIC; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; SOFTWARE;

EID: 79851510162     PISSN: 02197200     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219720011005252     Document Type: Article

References (35)

1. Lee J, Ban JY,Won KY, Kim GY, Lim SJ, Lee S, Kim YW, Park YK, Lee SS, Expression of EGFR and follicular dendritic markers in lymphoid follicles from patients with Castleman's disease, Oncol Rep 20:851-856, 2008.
2. Olman V, Hicks C, Wang P, Xu Y, Gene expression data analysis in subtypes of ovarian cancer using covariance analysis, J Bioinform Comput Biol 4:999-1014, 2006. (Pubitemid 44742256)
3. Saris CG, Horvath S, van Vught PW, van Es MA, Blauw HM, Fuller TF, Langfelder P, DeYoung J, Wokke JH, Veldink JH, van den Berg LH, Ophoff RA, Weighted gene co-expression network analysis of the peripheral blood from Amyotrophic Lateral Sclerosis patients, BMC Genomics 10:405, 2009.
4. Staub E, Groene J, Heinze M, Mennerich D, Roepcke S, Klaman I, Hinzmann B, Castanos-Velez E, Pilarsky C, Mann B, Brümmendorf T, Weber B, Buhr HJ, Rosenthal A, An expression module of WIPF1-coexpressed genes identifies patients with favorable prognosis in three tumor types, J Mol Med 87:633-644, 2009.
5. Aburatani S, Sun F, Saito S, Honda M, Kaneko S, Horimoto K, Gene systems network inferred from expression profiles in hepatocellular carcinogenesis by graphical Gaussian model, EURASIP J Bioinform Syst Biol 2007:47214, 2007.
6. Gao Z, Barth AS, DiSilvestre D, Akar FG, Tian Y, Tanskanen A, Kass DA, Winslow RL, Tomaselli GF, Key pathways associated with heart failure development revealed by gene networks correlated with cardiac remodeling, Physiol Genomics 35:222-230, 2008. (Pubitemid 352790812)
7. Stuart JM, Segal E, Koller D, Kim SK, A gene-coexpression network for global discovery of conserved genetic modules, Science 302:249-255, 2003. (Pubitemid 37248749)
8. Grieve IC, Dickens NJ, Pravenec M, Kren V, Hubner N, Cook SA, Aitman TJ, Petretto E, Mangion J, Genome-wide co-expression analysis in multiple tissues, PLoS One 3:e4033, 2008.
9. Allocco DJ, Kohane IS, Butte AJ, Quantifying the relationship between co-expression, co-regulation and gene function, BMC Bioinformatics 5:18, 2004.
10. Yeung KY, Medvedovic M, Bumgarner RE, From co-expression to co-regulation: How many microarray experiments do we need? Genome Biol 5:R48, 2004.
11. Langfelder P, Zhang B, Horvath S, Defining clusters from a hierarchical cluster tree: The Dynamic Tree Cut package for R, Bioinformatics 24:719-720, 2008. (Pubitemid 351321220)
12. Yan X, Mehan MR, Huang Y, Waterman MS, Yu PS, Zhou XJ, A graph-based approach to systematically reconstruct human transcriptional regulatory modules, Bioinformatics 23:i577-i586, 2007. (Pubitemid 47244445)
13. Zhang B, Horvath S, A general framework for weighted gene co-expression network analysis, Stat Appl Genet Mol Biol 4:Article17, 2005.
14. Langfelder P, Horvath S, Eigengene networks for studying the relationships between co-expression modules, BMC Syst Biol 1:54, 2007.
15. Chipman H, Tibshirani R, Hybrid hierarchical clustering with applications to microarray data, Biostatistics 7:286-301, 2006.
16. Langfelder P, Horvath S, WGCNA: An R package for weighted correlation network analysis, BMC Bioinformatics 9:559, 2008.
17. Gregg JP, Lit L, Baron CA, Hertz-Picciotto I, Walker W, Davis RA, Croen LA, Ozonoff S, Hansen R, Pessah IN, Sharp FR, Gene expression changes in children with autism, Genomics 91:22-29, 2008. (Pubitemid 350298392)
18. Jiang X, Tan J, Li J, Kivimäe S, Yang X, Zhuang L, Lee PL, Chan MT, Stanton LW, Liu ET, Cheyette BN, Yu Q, DACT3 is an epigenetic regulator of Wnt/beta-catenin signaling in colorectal cancer and is a therapeutic target of histone modifications, Cancer Cell 13(6):529-541, 2008. (Pubitemid 351766796)
19. Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik J, Hothorn T, HuberW, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JY, Zhang J, Bioconductor: Open software development for computational biology and bioinformatics, Genome Biol 5:R80, 2004.
20. Huang DW, Sherman BT, Lempicki RA, Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources, Nature Protocols 4:44-57, 2009.
21. Yip AM, Horvath S, Gene network interconnectedness and the generalized topological overlap measure, BMC Bioinformatics 8:22, 2007.
22. Li A, Horvath S, Network module detection: Affinity search technique with the multinode topological overlap measure, BMC Res Notes 2:142, 2009.
23. Zhou H, Distance, dissimilarity index, and network community structure, Phys Rev E 67:061901, 2003.
24. Wildenhain J, Crampin EJ, Reconstructing gene regulatory networks: From random to scale-free connectivity, Syst Biol (Stevenage) 153:247-256, 2006. (Pubitemid 44151484)
25. Xu Y, Olman V, Xu D, Clustering gene expression data using a graph-theoretic approach: An application of minimum spanning trees, Bioinformatics 18:536-545, 2002. (Pubitemid 34521043)
26. Kruskal JB, On the shortest spanning tree of a graph and the traveling salesman problem, in Proceedings of the American Mathematical Society, pp. 48-50, 1956.
27. Csardi G, Nepusz T, The igraph software package for complex network research, InterJournal: Complex Systems, 1965, 2006.
28. Horvath S, Dong J, Geometric interpretation of gene coexpression network analysis, PLoS Comput Biol 4:e1000117, 2008.
29. Chang SJ, Huang TS, Wang KL, Wang TY, Yang YC, Chang MD, Wu YH, Wang HW, Genetic network analysis of human CD34+ hematopoietic stem/precursor cells, Taiwan J Obstet Gynecol 47:422-430, 2008.
30. Dezso Z, Nikolsky Y, Sviridov E, Shi W, Serebriyskaya T, Dosymbekov D, Bugrim A, Rakhmatulin E, Brennan RJ, Guryanov A, Li K, Blake J, Samaha RR, Nikolskaya T, A comprehensive functional analysis of tissue specificity of human gene expression, BMC Biol 6:49, 2008.
31. Ma HW, Zhao XM, Yuan YJ, Zeng AP, Decomposition of metabolic network into functional modules based on the global connectivity structure of reaction graph, Bioinformatics 20:1870-1876, 2004.
32. Do JH, Choi DK, Clustering approaches to identifying gene expression patterns from DNA microarray data, Mol Cells 25:279-288, 2008. (Pubitemid 351819007)
33. Richards AL, Holmans P, O'Donovan MC, Owen MJ, Jones L, A comparison of four clustering methods for brain expression microarray data, BMC Bioinformatics 9:490, 2008.
34. Sherlock G, Analysis of large-scale gene expression data, Curr Opin Immunol 12: 201-205, 2000. (Pubitemid 30133111)
35. Thalamuthu A, Mukhopadhyay I, Zheng X, Tseng GC, Evaluation and comparison of gene clustering methods in microarray analysis, Bioinformatics 22:2405-2412, 2006. (Pubitemid 44566970)