Analysis of gene coexpression by B-spline based CoD estimation

Eurasip Journal on Bioinformatics and Systems Biology

Volumn 2007, Issue , 2007, Pages

  Li, Huai ^a   Sun, Yu ^a   Zhan, Ming ^a  

^a NATIONAL INSTITUTE ON AGING   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 34247188062     PISSN: 16874145     EISSN: 16874153     Source Type: Journal    
DOI: 10.1155/2007/49478     Document Type: Article

References (29)

1. J. M. Stuart E. Segal D. Koller koller@cs.stanford.edu S. K. Kim kim@cmgm.stanford.edu A gene-coexpression network for global discovery of conserved genetic modules. Science 302 5643 2003 249 255
2. H. K. Lee A. K. Hsu J. Sajdak J. Qin P. Pavlidis pp175@columbia.edu Coexpresion analysis of human genes across many microarray data sets. Genome Research 14 6 2004 1085 1094
3. V. van Noort B. Snel M. A. Huynen m.huynen@cmbi.kun.nl The yeast coexpression network has a small-world, scale-free architecture and can be explained by a simple model. EMBO Reports 5 3 2004 280 284
4. S. L. Carter C. M. Brechbûhler M. Griffin A. T. Bond abond@xpogen.com Gene co-expression network topology provides a framework for molecular characterization of cellular state. Bioinformatics 20 14 2004 2242 2250
5. T. G. Graeber D. Eisenberg Bioinformatic identification of potential autocrine signaling loops in cancers from gene expression profiles. Nature Genetics 29 3 2001 295 300
6. M. J. Herrgård M. W. Covert B. Palsson palsson@ucsd.edu Reconciling gene expression data with known genome-scale regulatory network structures. Genome Research 13 11 2003 2423 2434
7. S. Imoto T. Goto S. Miyano Estimation of genetic networks and functional structures between genes by using Bayesian networks and nonparametric regression. Pacific Symposium on Biocomputing 2002 175 186
8. A. J. Butte I. S. Kohane Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements. Pacific Symposium on Biocomputing 2000 418 429
9. X. Zhou X. Wang E. R. Dougherty edward@ee.tamu.edu Construction of genomic networks using mutual-information clustering and reversible-jump Markov-chain-Monte-Carlo predictor design. Signal Processing 83 4 2003 745 761
10. S. Kim dolchan@nih.gov H. Li E. R. Dougherty Can Markov chain models mimic biological regulation? Journal of Biological Systems 10 4 2002 337 357
11. R. F. Hashimoto S. Kim I. Shmulevich W. Zhang M. L. Bittner E. R. Dougherty e-dougherty@tamu.edu Growing genetic regulatory networks from seed genes. Bioinformatics 20 8 2004 1241 1247
12. I. Shmulevich E. R. Dougherty S. Kim W. Zhang Probabilistic Boolean networks: a rule-based uncertainty model for gene regulatory networks. Bioinformatics 18 2 2002 261 274
13. E. R. Dougherty e-daughesty@tanu.edu S. Kim Y. Chen Coefficient of determination in nonlinear signal processing. Signal Processing 80 10 2000 2219 2235
14. H. Li M. Zhan zhanmi@mail.nih.gov Systematic intervention of transcription for identifying network response to disease and cellular phenotypes. Bioinformatics 22 1 2006 96 102
15. V. Hatzimanikatis K. H. Lee Dynamical analysis of gene networks requires both mRNA and protein expression information. Metabolic Engineering 1 4 1999 275 281
16. H. Prautzsch W. Boehm M. Paluszny Bézier and B-Spline Techniques. Springer Berlin, Germany 2002
17. P. Ma C. I. Castillo-Davis W. Zhong J. S. Liu jliu@stat.harvard.edu A data-driven clustering method for time course gene expression data. Nucleic Acids Research 34 4 2006 1261 1269
18. J. D. Storey jstorey@u.washington.edu W. Xiao J. T. Leek R. G. Tompkins R. W. Davis dbowe@stanford.edu Significance analysis of time course microarray experiments. Proceedings of the National Academy of Sciences of the United States of America 102 36 2005 12837 12842
19. Z. Bar-Joseph zivbj@mit.edu G. K. Gerber D. K. Gifford T. S. Jaakkola I. Simon Continuous representations of time-series gene expression data. Journal of Computational Biology 10 3-4 2003 341 356
20. K. Bhasi A. Forrest M. Ramanathan murali@acsu.buffalo.edu SPLINDID: a semi-parametric, model-based method for obtaining transcription rates and gene regulation parameters from genomic and proteomic expression profiles. Bioinformatics 21 20 2005 3873 3879
21. W. He he@mshri.on.ca A spline function approach for detecting differentially expressed genes in microarray data analysis. Bioinformatics 20 17 2004 2954 2963
22. Y. Luan H. Li hli@ucdavis.edu Clustering of time-course gene expression data using a mixed-effects model with B-splines. Bioinformatics 19 4 2003 474 482
23. C. O. Daub R. Steuer J. Selbig S. Kloska Estimating mutual information using B-spline functions - an improved similarity measure for analysing gene expression data. BMC Bioinformatics 5 1 2004 118
24. R. A. Irizarry B. M. Bolstad F. Collin L. M. Cope B. Hobbs T. P. Speed Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Research 31 4 2003 e15
25. P. W. Lord p.lord@russet.org.uk R. D. Stevens A. Brass C. A. Goble Investigating semantic similarity measures across the gene ontology: the relationship between sequence and annotation. Bioinformatics 19 10 2003 1275 1283
26. K. D. Brubaker E. Corey L. G. Brown R. L. Vessella vessella@u.washington. edu Bone morphogenetic protein signaling in prostate cancer cell lines. Journal of Cellular Biochemistry 91 1 2004 151 160
27. S. Yang C. Zhong B. Frenkel A. H. Reddi P. Roy-Burman royburma@usc.edu Diverse biological effect and Smad signaling of bone morphogenetic protein 7 in prostate tumor cells. Cancer Research 65 13 2005 5769 5777
28. A. Müller B. Homey H. Soto Involvement of chemokine receptors in breast cancer metastasis. Nature 410 6824 2001 50 56
29. J. M. Wang X. Deng W. Gong S. Su Chemokines and their role in tumor growth and metastasis. Journal of Immunological Methods 220 1-2 1998 1 17