Analysis of nonlinear relations between expression profiles by the principal curves of oriented-points approach

Journal of Bioinformatics and Computational Biology

Volumn 6, Issue 2, 2008, Pages 367-386

  Huerta, Mario ^a   Cedano, Juan ^a   Querol, Enrique ^a  

^a UNIVERSITAT AUTÒNOMA DE BARCELONA   (Spain)

Author keywords

Gene networks; Microarrays; Principal curve analysis

Indexed keywords

ANALYTIC METHOD; ARTICLE; DNA MICROARRAY; GENE EXPRESSION; GENETIC SELECTION; HIGH THROUGHPUT SCREENING; MATHEMATICAL ANALYSIS; MOLECULAR PHYLOGENY; NONLINEAR SYSTEM;

GENE EXPRESSION; GENE EXPRESSION PROFILING; HUMANS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; SEQUENCE ALIGNMENT;

EID: 44149110589     PISSN: 02197200     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219720008003394     Document Type: Article

References (42)

1. D'Haeseleer P, Liang S, Somogyi R, Genetic network inference: From co-expression clustering to reverse engineering, Bioinformatics 16:707-726, 2000.
2. Thieffry D, Thomas R. Qualitative analysis of gene networks, Pac Symp Biocomput: 77-88, 1998.
3. Heidtke KR, Schulze-Kremer S, Design and implementation of a qualitative simulation model of lambda phage infection, Bioinformatics 14 81-91, 1998.
4. Vu TT, Vohradsky J, Genexp - A genetic network simulation environment, Bioinformatics 18:1400-1401, 2002.
5. Vohradsky J, Neural network model of gene expression, FASEB J 15:846-854, 2001.
6. Wessels LF, van Someren EP, Reinders MJ, A comparison of genetic network models, Pac Symp Biocomput:508-519, 2001.
7. Mestl T, Plahte E, Omholt SW, A mathematical framework for describing and analysing gene regulatory networks, J Theor Biol 176 291-300, 1995.
8. Becskei A, Serrano L, Engineering stability in gene networks by autoregulation, Nature 405:590-593, 2000.
9. Goryanin I, Hodgman TC, Selkov E, Mathematical simulation and analysis of cellular metabolism and regulation, Bioinformatics 15 749-758, 1999.
10. Arkin A, Ross J, McAdams HH, Stochastic kinetic analysis of developmental pathway bifurcation in phage lambda-infected Escherichia coli cells, Genetics 149:1633-1648, 1998.
11. McAdams HH, Arkin A, Stochastic mechanisms in gene expression, Proc Natl Acad Sci USA 94:814-819, 1997.
12. Kastner J, Solomon J, Fraser S, Modeling a hox gene network in silico using a stochastic simulation algorithm, Dev Biol 246 122-131, 2002.
13. Wong P, Gladney S, Keasling JD, Mathematical model of the lac operbn: Inducer exclusion, catabolite repression, and diauxic growth on glucose and lactose, Biotechnol Prog 13:132-143, 1997.
14. Swain PS, Elowitz MB, Siggia ED, Intrinsic and extrinsic contributions to stochasticity in gene expression, Proc Natl Acad Sci USA 99 12795-12800, 2002.
15. Rosenfeld N, Elowitz MB, Alon U, Negative autoregulation speeds the response times of transcription networks, J Mol Biol 323 785-793, 2002.
16. Guet CC, Elowitz MB, Hsing W, Leibler S, Combinatorial synthesis of genetic networks, Science 296:1466-1470, 2002.
17. Mao L, Resat H, Probabilistic representation of gene regulatory networks, Bioinformatics 20:2258-2269, 2004.
18. Weaver DC, Workman CT, Stormo GD, Modeling regulatory networks with weight matrices, Pac Symp Biocomput:112-123, 1999.
19. Davidson EH et al., A genomic regulatory network for development, Science 295:1669-1678, 2002.
20. Delicado P, Huerta M, Principal curves of oriented points: Theoretical and computational improvements, Comput Stat 18:293-315, 2003.
21. Delicado P, Another look at principal curves and surfaces, J Multivar Anal 77:84-116, 2001.
22. Hastie T, Stuetzle W, Principal curves, J Am Stat Assoc 84 502-516, 1989.
23. Chang K, Ghosh J, A unified model for probabilistic principal surfaces, IEEE Trans Pattern Anal Mach Intell 23:22-41, 2001.
24. Kegl B, Krzyzak A, Linder T, Zeger K, Learning and design of principal curves, IEEE Trans Pattern Anal Mach Intell 22:281-297, 2000.
25. Sandilya S, Kulkarni SR, Principal curves with bounded turn, IEEE Trans Inf Theory 48:2789-2793, 2002.
26. Mulier F, Cherkassky V, Self-organization as an iterative kernel smoothing process, Neural Comput 7:1165-1177, 1995.
27. Dong D, McAvoy TJ, Nonlinear principal component analysis - Based on principal curves and neural networks, Comput Chem Eng 20 65-78, 1996.
28. Delicado P, Huerta M, Principal curves of oriented points: Theoretical and computational improvements, Technical Report, EIO-UPC, Universitat Politecnica de Catalunya, Barcelona, Spain, 2002.
29. Scherf U et al., A gene expression database for the molecular pharmacology of cancer, Nat Genet 24:236-244, 2000.
30. Eisen MB, Spellman PT, Brown PO, Botstein D, Cluster analysis and display of genome-wide expression patterns, Proc Natl Acad Sci USA 95:14863-14868, 1998.
31. Alon U et al., Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays, Proc Natl Acad Sci USA 96:6745-6750, 1999.
32. Hartigan JA, Consistency of single linkage for high-density clusters, J Am Stat Assoc 76:388-394, 1981.
33. Gower JC, Ross GJS, Minimum spanning trees and single linkage cluster analysis, J R Stat Soc Ser C Appl Stat 18:54-64, 1969.
34. Chen J et al., Contribution of p161NK4a and p21CIP1 pathways to induction of premature senescence of human endothelial cells: Permissive role of p53, Am J Physiol Heart Circ Physiol 290 H1575-H1586, 2006.
35. Hinchcliffe EH, Li C, Thompson EA, Maller JL, Sluder G, Requirement of Cdk2-cyclin E activity for repeated centrosome reproduction in Xenopus egg extracts, Science 283:851-854, 1999.
36. Bielas JH, Heddle JA, Elevated mutagenesis and decreased DNA repair at a transgene are associated with proliferation but not apoptosis in p53-deficient cells, Proc Natl Acad Sci USA 100:12853-12858, 2003.
37. Spruck CH, Won KA, Reed SI, Deregulated cyclin E induces chromosome instability, Nature 401:297-300, 1999.
38. Tissier F et al., Cyclin E correlates with malignancy and adverse prognosis in adreno-cortical tumors, Eur J Endocrinol 150 809-817, 2004.
39. Sullivan DC et al., EndoPDI, a novel protein-disulfide isomerase-like protein that is preferentially expressed in endothelial cells acts as a stress survival factor, J Biol Chem 278 47079-47088, 2003.
40. Knoblach B et al., ERp19 and ERp46, new members of the thioredoxin family of endoplasmic reticulum proteins, Mol Cell Proteomics 2 1104-1119, 2003.
41. Tu Y, Stolovitzky G, Klein U, Quantitative noise analysis for gene expression microarray experiments, Proc Natl Acad Sci USA 99 14031-14036, 2002.
42. Ashburner M et al., Gene Ontology: Tool for the unification of biology. The Gene Ontology Consortium, Nat Genet 25:25-29, 2000.