Rank-based edge reconstruction for scale-free genetic regulatory networks

BMC Bioinformatics

Volumn 9, Issue , 2008, Pages

  Chen, Guanrao ^a   Larsen, Peter ^b   Almasri, Eyad ^c   Dai, Yang ^c  

^a 1120 Science and Engineering Offices   (United States)

^b UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

^c University of Illinois at Chicago   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DEGREE DISTRIBUTIONS; EDGE RECONSTRUCTION; GENETIC REGULATORY NETWORKS; MICROARRAY GENE EXPRESSION DATA; NETWORK RECONSTRUCTION; RANK-BASED ALGORITHM; SCALE-FREE TOPOLOGIES; TOPOLOGICAL CHARACTERISTICS;

BAYESIAN NETWORKS; BIOINFORMATICS; GENE EXPRESSION; TOPOLOGY;

ALGORITHMS;

ARTICLE; BAYES THEOREM; CELL CYCLE; CONTROLLED STUDY; GENE CONTROL; GENE EXPRESSION PROFILING; GENETIC ALGORITHM; GENETIC ANALYSIS; INTERMETHOD COMPARISON; MICROARRAY ANALYSIS; NONHUMAN; SAMPLE SIZE; SIMULATION; YEAST; ALGORITHM; BIOLOGICAL MODEL; COMPUTER SIMULATION; DNA MICROARRAY; GENE EXPRESSION REGULATION; METABOLISM; METHODOLOGY; PHYSIOLOGY; SIGNAL TRANSDUCTION;

PROTEOME;

ALGORITHMS; COMPUTER SIMULATION; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; MODELS, BIOLOGICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PROTEOME; SIGNAL TRANSDUCTION;

EID: 41349112109     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-9-75     Document Type: Article

References (53)

1. Liang S Fuhrman S Somogyi R Reveal, a general reverse engineering algorithm for inference of genetic network architectures Pac Symp Biocomput 1998:18-29. 9697168
2. Murphy KP Mian S Modeling gene expression data using dynamic Bayesian networks Technical report University of California at Berkeley. Berkeley, CA 1999
3. Akutsu T Miyano S Kuhara S Identification of genetic networks from a small number of gene expression patterns under the Boolean network model Pac Symp Biocomput 1999:17-28. 10380182
4. D'Haeseleer P Liang S Somogyi R Genetic network inference: From co-expression clustering to reverse engineering Bioinformatics 2000, 16(8):707-726. 11099257
5. Friedman N Linial M Nachman I Pe'er D Using Bayesian networks to analyze expression data J Comput Biol 2000, 7:601. 11108481
6. Ideker TE Thorsson V Karp RM Discovery of regulatory interactions through perturbation: Inference and experimental design Pac Symp Biocomput 2000:305-316. 10902179
7. Pe'er D Regev A Elidan G Friedman N Inferring subnetworks from perturbed expression profiles Bioinformatics 2001 17 Suppl 1:S215-24. 11473012
8. Imoto S Goto T Miyano S Estimation of genetic networks and functional structures between genes by using Bayesian networks and nonparametric regression Pac Symp Biocomput 2002:175-186. 11928473
9. Yu J Smith VA Wang PP Hartemink AJ Jarvis ED Advances to Bayesian network inference for generating causal networks from observational biological data Bioinformatics 2004, 20(18):3594-3603. 15284094
10. Bernard A Hartemink AJ Informative structure priors: Joint learning of dynamic regulatory networks from multiple types of data Pac Symp Biocomput 2005:459-470. 15759651
11. de Hoon MJL Imoto S Kobayashi K Ogasawara N Miyano S Inferring gene regulatory networks from time-ordered gene expression data of Bacillus subtilis using differential equations Pac Symp Biocomput 2003, 8:17-28
12. Chen T He HL Church GM Modeling gene expression with differential equations Pacific Symposium on Biocomputing 1999, 4:29-40
13. Kimura S Ide K Kashihara A Kano M Hatakeyama M Masui R Nakagawa N Yokoyama S Kuramitsu S Konagaya A Inference of S-system models of genetic networks using a cooperative coevolutionary algorithm Bioinformatics 2005, 21(7):1154-1163. 15514004
14. di Bernardo D Thompson MJ Gardner TS Chobot SE Eastwood EL Wojtovich AP Elliott SJ Schaus SE Collins JJ Chemogenomic profiling on a genome-wide scale using reverse-engineered gene networks Nat Biotech 2005, 23(3):377.
15. Chen KC Wang TY Tseng HH Huang CYF Kao CY A stochastic differential equation model for quantifying transcriptional regulatory network in Saccharomyces cerevisiae Bioinformatics 2005, 21(12):2883-2890. 15802287
16. Yeung MK Tegner J Collins JJ Reverse engineering gene networks using singular value decomposition and robust regression Proc Natl Acad Sci USA 2002, 99:6163 122920 11983907
17. Wang W Cherry JM Botstein D Li H A systematic approach to reconstructing transcription networks in Saccharomycescerevisiae PNAS 2002, 99(26):16893-16898. 139240 12482955
18. Stuart JM Segal E Koller D Kim SK A Gene-Coexpression Network for Global Discovery of Conserved Genetic Modules Science 2003, 302(5643):249-255. 12934013
19. Segal E Shapira M Regev A Pe'er D Botstein D Koller D Friedman N Module networks: Identifying regulatory modules and their condition-specific regulators from gene expression data Nat Genet 2003, 34(2):166. 12740579
20. Liao JC Boscolo R Yang YL Tran LM Sabatti C Roychowdhury VP Network component analysis: Reconstruction of regulatory signals in biological systems Proc Natl Acad Sci U S A 2003, 100(26):15522-15527. 14673099 14673099 307600
21. Gardner TS di Bernardo D Lorenz D Collins JJ Inferring genetic networks and identifying compound mode of action via expression profiling Science 2003, 301:102 12843395
22. Xing B van der Laan MJ A causal inference approach for constructing transcriptional regulatory networks Bioinformatics 2005, 21(21):4007-4013. 16131521
23. Xing B van der Laan MJ A Statistical Method for Constructing Transcriptional Regulatory Networks Using Gene Expression and Sequence Data Journal of Computational Biology 2005, 12(2):229-246. 15767778
24. Yu T Li KC Inference of transcriptional regulatory network by two-stage constrained space factor analysis Bioinformatics 2005, 21(21):4033-4038. 16144806
25. Li SP Tseng JJ Wang SC Reconstructing gene regulatory networks from time-series microarray data Physica A: Statistical and Theoretical Physics 2005, 350(1):63.
26. Sanguinetti G Rattray M Lawrence ND A probabilistic dynamical model for quantitative inference of the regulatory mechanism of transcription Bioinformatics 2006, 22(14):1753-1759. 16632490
27. Faith JJ Hayete B Thaden JT Mogno I Wierzbowski J Cottarel G Kasif S Collins JJ Gardner TS Large-Scale Mapping and Validation of Escherichia coli Transcriptional Regulation from a Compendium of Expression Profiles PLoS Biology 2007, 5(1):e8. 1764438 17214507
28. de Jong H Modeling and simulation of genetic regulatory systems: A literature review J Comput Biol 2002, 9(1):67-103. 11911796
29. Hartemink AJ Gifford DK Jaakkola TS Young RA Combining location and expression data for principled discovery of genetic regulatory network models Pac Symp Biocomput 2002:437-449. 11928497
30. Tamada Y Kim S Bannai H Imoto S Tashiro K Kuhara S Miyano S Estimating gene networks from gene expression data by combining Bayesian network model with promoter element detection Bioinformatics 2003, 19 Suppl 2:II227-II236. 14534194
31. Yeang CH Ideker T Jaakkola T Physical Network Models Journal of Computational Biology 2004, 11(2-3):243-262. 15285891
32. Le Phillip P Bahl A Unga LH Using prior knowledge to improve genetic network reconstruction from microarray data In Silico Biology 2004, 4:335-353. 15724284 15724284
33. Zou M Conzen SD A new dynamic Bayesian network (DBN) approach for identifying gene regulatory networks from time course microarray data Bioinformatics 2005, 21(1):71-79. 15308537
34. Lee PH Lee D Modularized learning of genetic interaction networks from biological annotations and mRNA expression data Bioinformatics 2005, 21:2739-2747. 15797909 15797909
35. Geier F Timmer J Fleck C Reconstructing gene-regulatory networks from time series, knock-out data, and prior knowledge BMC Systems Biology 2007, 1(1):11. 1839889 17408501
36. Albert R Barabási AL Statistical mechanics of complex networks Reviews of Modern Physics American Physical Society 2002, 74(1):47
37. Farkas I Jeong H Vicsek T Barabasi AL Oltvai ZN The topology of the transcription regulatory network in the yeast, Saccharomyces cerevisiae Physica A 2003, 318(3-4):601-612
38. Barabasi AL Oltvai ZN Network biology: Understanding the cell's functional organization Nature Reviews Genetics 2004, 5(2):101-113. 14735121
39. Daisuke T Horton P Inference of scale-free networks from gene expression time series J Bioinform Comput Biol. 2006, 4:503-514. 16819798 16819798
40. Baiesi M Manna SS Scale-free networks from a Hamiltonian dynamics Physical Review E American Physical Society 2003, 68(4):47103
41. Louzoun Y Muchnik L Solomon S Copying nodes versus editing links: The source of the difference between genetic regulatory networks and the WWW Bioinformatics 2006, 22(5):581-588. 16403796
42. Agrawal H Extreme Self-Organization in Networks Constructed from Gene Expression Data Physical Review Letters American Physical Society 2002, 89(26):268702. 12484863
43. Huttenhower C Flamholz A Landis J Sahi S Myers C Olszewski K Hibbs M Siemers N Troyanskaya O Coller H Nearest Neighbor Networks: Clustering expression data based on gene neighborhoods BMC Bioinformatics 2007, 8(1):250. 1941745 17626636
44. Spellman PT Sherlock G Zhang MQ Iyer VR Anders K Eisen MB Brown PO Botstein D Futcher B Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization Mol Biol Cell 1998, 9(12):3273-3297. 25624 9843569
45. Nikitin A Egorov S Daraselia N Mazo I Pathway studio - the analysis and navigation of molecular networks Bioinformatics 2003, 19(16):2155-2157. 14594725
46. GO Slim Mapper http://db.yeastgenome.org/cgi-bin/GO/goTermMapper
47. Myers C Robson D Wible A Hibbs M Chiriac C Theesfeld C Dolinski K Troyanskaya O Discovery of biological networks from diverse functional genomic data Genome Biology 2005, 6(13):R114. 1414113 16420673
48. Myers C Barrett D Hibbs M Huttenhower C Troyanskaya O Finding function: evaluation methods for functional genomic data BMC Genomics 2006, 7(1):187. 1560386 16869964
49. Myers CL Troyanskaya OG Context-sensitive data integration and prediction of biological networks Bioinformatics 2007, 23(17):2322-2330. 17599939
50. Battle A Segal E Koller D Probabilistic Discovery of Overlapping Cellular Processes and Their Regulation Journal of Computational Biology 2005, 12(7):909-927. 16201912
51. Larsen P Almasri E Chen G Dai Y A statistical method to incorporate biological knowledge for generating testable novel gene regulatory interactions from microarray experiments BMC Bioinformatics 2007, 8:317. 2082045 17727721
52. Matlab fit() function http://www.mathworks.com/access/helpdesk/help/ toolbox/curvefit/fit.html
53. He F Zeng AP In search of functional association from time-series microarray data based on the change trend and level of gene expression BMC Bioinformatics 2006, 7(1):69. 1435774 16478547