Overview of computational methods for the inference of gene regulatory networks

Computers and Chemical Engineering

Volumn 29, Issue 3, 2005, Pages 519-534

  Styczynski, Mark P ^a   Stephanopoulos, Gregory ^a  

^a Massachusetts Institute of Technology Cambridge   (United States)

Author keywords

Binding site discovery; cis Regulatory networks; GRN; Systems biology; TFBS

Indexed keywords

CELLS; COMPUTATIONAL METHODS; DATA REDUCTION; GENETIC ENGINEERING; REVERSE ENGINEERING;

CELLULAR PHENOTYPES; GENE REGULATORY NETWORKS (GRN); PATTERN DISCOVERY;

GENES;

DNA; MESSENGER RNA; PRIMER DNA; TRANSCRIPTION FACTOR;

BIOCHEMICAL ENGINEERING;

BAYES THEOREM; DNA SEQUENCE; GENE ACTIVATION; GENE ACTIVITY; GENE CONTROL; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE REPRESSION; GENE SEQUENCE; GENETIC ALGORITHM; GENETIC ENGINEERING; MODEL; PHENOTYPE; PROMOTER REGION; REVIEW; SEQUENCE ALIGNMENT;

EID: 15744367955     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compchemeng.2004.08.029     Document Type: Article

References (77)

1. S. Aerts, G. Thijs, B. Coessens, M. Staes, Y. Moreau, and B. De Moor Toucan: deciphering the cis-regulatory logic of coregulated genes Nucleic Acids Research 31 2003 1753 1764
2. D.M. Allen The relationship between variable selection and data augmentation and a method for prediction Technometrics 16 1974 125 127
3. S.F. Altschul, T.L. Madden, A.A. Schaffer, J. Zhang, Z. Zhang, W. Miller, and D.J. Lipman Gapped BLAST and PSI-BLAST: A new generation of protein database search programs Nucleic Acids Research 25 1997 3389 3402
4. S. Ando, E. Sakamoto, and H. Iba Evolutionary modeling and inference of gene network Information Sciences 145 2002 237 259
5. A. Arkin, J. Ross, and H.H. McAdams Stochastic kinetic analysis of developmental pathway bifurcation in phage lambda-infected Escherichia coli cells Genetics 149 1998 1633 1648
6. T.L. Bailey, and C. Elkan Fitting a mixture model by expectation maximization to discover motifs in biopolymers Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology 1994 28 36
7. M. Blanchette, and M. Tompa Discovery of regulatory elements by a computational method for phylogenetic footprinting Genome Research 12 2002 739 748
8. H. Bolouri, and E.H. Davidson Modeling transcriptional regulatory networks Bioessays 24 2002 1118 1129
9. N. Bray, I. Dubchak, and L. Pachter AVID: A global alignment program Genome Research 13 2003 97 102
10. T. Chen, V. Filkox, and S.S. Skiena Identifying gene regulatory networks from experimental data Parallel Computing 27 2001 141 162
11. J.L. Cherry, and F.R. Adler How to make a biological switch Journal of Theoretical Biology 203 2000 117 133
12. W.H.E. Day, and F.R. McMorris Critical comparison of consensus methods for molecular sequences Nucleic Acids Research 20 1992 1093 1099
13. M. de Hoon, S. Imoto, and S. Miyano Inferring gene regulatory networks from time-ordered gene expression data using differential equations Lecture Notes in Computer Science 2534 2002 267 274
14. P. D'haeseleer, S.D. Liang, and R. Somogyi Genetic network inference: From coexpression clustering to reverse engineering Bioinformatics 16 2000 707 726
15. E.R. Dougherty, S. Kim, and Y.D. Chen Coefficient of determination in nonlinear signal processing Signal Processing 80 2000 2219 2235
16. I. Dubchak, M. Brudno, G.G. Loots, C. Mayor, L. Pachter, E.M. Rubin, and K.A. Frazer Active conservation of noncoding sequences revealed by 3-way species comparisons Genome Research 10 2000 1304 1306
17. K. Ellrott, C. Yang, F.M. Sladek, and T. Jiang Identifying transcription factor binding sites through Markov chain optimization Bioinformatics 18 2002 S100 S109
18. D.E. Featherstone, and K. Broadie Wrestling with pleiotropy: Genomic and topological analysis of the yeast gene expression network BioEssays 24 2002 267 274
19. N. Friedman, M. Linial, I. Nachman, and D. Pe'er Using Bayesian networks to analyze expression data Journal of Computational Biology 7 2000 601 620
20. T.S. Gardner, D. di Bernardo, D. Lorenz, and J.J. Collins Inferring genetic networks and identifying compound mode of action via expression profiling Science 301 2003 102 105
21. D. GuhaThakurta, and G.D. Stormo Identifying target sites for cooperatively binding factors Bioniformatics 17 2001
22. M. Gupta, and J.S. Liu Discovery of conserved sequence patterns using a stochastic dictionary model Journal of the American Statistical Association 98 2003 55 66
23. A.J. Hartemink, D.K. Gifford, T.S. Jaakkola, and R.A. Young Bayesian methods for elucidating genetic regulatory networks IEEE Intelligent Systems 17 2002 37 43
24. J. Hasty, D. McMillen, F. Isaacs, and J.J. Collins Computational studies of gene regulatory networks: In numero molecular biology Nature Reviews: Genetics 2 2001 268 279
25. D. Heckerman, D. Geiger, and D.M. Chickering Learning Bayesian networks: The combination of knowledge and statistical data Machine Learning 20 1995 197 243
26. J. Herrero, R. Diaz-Uriarte, and J. Dopazo An approach to inferring transcriptional regulation among genes from large-scale expression data Comparative and Functional Genomics 4 2003 148 154
27. J.D. Hughes, P.W. Estep, S. Tavazoie, and G.M. Church Computational identification of cis-regulatory elements associated with groups of functionally related genes in Saccharomyces cerevisiae Journal of Molecular Biology 296 2000 1205 1214
28. T.R. Hughes, M.J. Marton, A.R. Jones, C.J. Roberts, R. Stoughton, C.D. Armour, H.A. Bennett, E. Coffey, H.Y. Dai, Y.D.D. He, M.J. Kidd, A.M. King, M.R. Meyer, D. Slade, P.Y. Lum, S.B. Stepaniants, D.D. Shoemaker, D. Gachotte, K. Chakraburtty, J. Simon, M. Bard, and S.H. Friend Functional discovery via a compendium of expression profiles Cell 102 2000 109 126
29. H. Iba, and A. Mimura Inference of a gene regulatory network by means of interactive evolutionary computing Information Sciences 145 2002 225 236
30. T.S. Jaakkola, and M.I. Jordan Variational probabilistic inference and the QMR-DT database Journal of Artificial Intelligence Research 10 1999 291 322
31. T.B. Kepler, and T.C. Elston Stochasticity in transcriptional regulation: Origins, 35 consequences, and mathematical representations Biophysical Journal 81 2001 3116 3136
32. S.C. Kim, E.R. Dougherty, M.L. Bittner, Y.D. Chen, K. Sivakumar, P. Meltzer, and J.M. Trent General nonlinear framework for the analysis of gene interaction via multivariate expression arrays Journal of Biomedical Optics 5 2000 411 424
33. S.C. Kim, E.R. Dougherty, Y.D. Chen, K. Sivakumar, P. Meltzer, J.M. Trent, and M. Bittner Multivariate measurement of gene expression relationships Genomics 67 2000 201 209
34. P.A. Lachenbruch, and M.R. Mickey Estimation of error rates in discriminant analysis Technometrics 10 1968 1 11
35. C.E. Lawrence, S.F. Altschul, M.S. Boguski, J.S. Liu, A.F. Neuwald, and J.C. Wootton Detecting subtle sequence signals: A Gibbs sampling strategy for multiple alignment Science 262 1993 208 214
36. A. Lindlof, and B. Olsson Could correlation-based methods be used to derive genetic association networks? Information Sciences 146 2002 103 113
37. J.S. Liu The collapsed Gibbs sampler in Bayesian computations with applications to a gene regulation problem Journal of the American Statistical Association 89 1994 958 966
38. J.S. Liu, A.F. Neuwald, and C.E. Lawrence Bayesian models for multiple local sequence alignment and Gibbs sampling strategies Journal of the American Statistical Association 90 1995 1156 1170
39. X.S. Liu, D.L. Brutlag, and J.S. Liu Bioprospector: Discovering conserved DNA motifs in upstream regulatory regions of co-expressed genes Proceedings of the Pacific Symposium on Biocomputing 2001 127 138
40. X.S. Liu, D.L. Brutlag, and J.S. Liu An algorithm for finding protein-DNA binding sites with applications to chromatin-immunoprecipitation microarray experiments Nature Biotechnology 20 2002 835 839
41. G.G. Loots, I. Ovcharenko, L. Pachter, I. Dubchak, and E.M. Rubin rVista for comparative sequence-based discovery of transcrition factor binding sites Genome Research 12 2002 832 839
42. Y. Luan, and H. Li Clustering of time-course gene expression data using a mixedeffects model with B-splines Bioinformatics 19 2003 474 482
43. C. Mayor, M. Brudno, J.R. Schwartz, A. Poliakov, E.M. Rubin, K.A. Frazer, L.S. Pachter, and I. Dubchak VISTA: Visualizing global DNA sequence alignments of arbitrary length Bioinformatics 16 2000 1046 1047
44. T. Mestl, E. Plahte, and S.W. Omholt A mathematical framework for describing and analysing gene regulatory networks J. Theor. Biol. 176 1995 291 300
45. Y. Moreau, F. De Smet, G. Thijs, K. Marchal, and B. De Moor Functional bioinformatics of microarray data: From expression to regulation Proceedings of the IEEE 90 2002 1722 1743
46. L. Parida, A. Floratos, and I. Rigoutsos An approximation algorithm for alignment of multiple sequences using motif discovery Journal of Combinatorial Optimization 3 1999 247 275
47. W.R. Pearson, and D.J. Lipman Improved tools for biological sequence comparison PNAS 85 1988 2444 2448
48. D. Pribnow Nucleotide sequence of an RNA polymerase binding site at an early T7 promoter PNAS 72 1975 784 788
49. P. Qui, W. Ding, Y. Jiang, J.R. Greene, and L. Wang Computational analysis of composite regulatory elements Mammalian Genome 13 2002 327 332
50. J. Reinitz, and D.H. Sharp Mechaninsm of eve stripe formation Mechanisms of Development 49 1995 133 158
51. D. Repsilber, Liljenstrom, and S.G.E. Andersson Reverse engineering of regulatory networks: Simulation studies on a genetic algorithm approach for ranking hypotheses BioSystems 66 2002 31 41
52. R. Rosen Recent developments in the theory of control and regulation of cellular processes G.H. Bourne International review of cytology 1968 Academic Press New York
53. J. Rung, T. Schlitt, A. Brazma, K. Freivalds, and J. Vilo Building and analysing genome-wide gene disruption networks Bioinformatics 18 2002 S202 S210
54. H. Salgado, A. Santos-Zavaleta, S. Gama-Castro, D. Millan-Zarate, E. Diaz-Peredo, F. Sanchez-Solano, E. Perez-Rueda, C. Bonavides-Martinez, and J. Collado-Vides RegulonDB (version 3.2): Transcriptional regulation and operon organization in Escherichia coli K-12 Nucleic Acids Research 29 2001 72 74
55. M.A. Savageau Rules for the evolution of gene circuity Pacific Symposium on Biocomputing 3 1998 54 65
56. E.E. Schadt, S.A. Monks, T.A. Drake, A.J. Lusis, N. Che, V. Collnayo, T.G. Ruff, S.B. Milligan, J.R. Lamb, G. Cavet, P.S. Linsley, M. Mao, R.B. Stoughton, and S.H. Friend Genetics of gene expression surveyed in maize, mouse and man Nature 422 2003 297 302
57. T. Schlitt, and A. Brazma Learning about gene regulatory networks from gene deletion experiments Comparative and Functional Genomics 3 2002 499 503
58. S. Schwartz, Z. Zhang, K.A. Frazer, A. Smit, C. Riemer, J. Bouck, R. Gibbs, R. Hardison, and W. Miller PipMaker - a web server for aligning two genomic DNA sequences Genome Research 10 2000 577 586
59. I. Shmulevich, E.R. Dougherty, S. Kim, and W. Zhang Probabilistic Boolean networks: A rule-based uncertainty model for gene regulatory networks Bioinformatics 18 2002 261 274
60. I. Shmulevich, E.R. Dougherty, and W. Zhang Gene perturbation and intervention in probabilistic Boolean networks Bioinformatics 18 2002 1319 1331
61. Smith, H. O., Hutchison, C. A., Pfannkoch, C., & Venter, J. C. (2003). Generating a synthetic genome by whole genome assembly: phi-X174 bacteriophage from synthetic oligonucleotides [on-line]. PNAS. Available: http://www.pnas.org/cgi/doi/10.1073/pnas.2237126100.
62. P. Smolen, D.A. Baxter, and J.H. Byrne Mathematical modeling of gene networks Neuron 26 2000 567 580
63. P. Smolen, D.A. Baxter, and J.H. Byrne Modeling transcriptional control in gene networks - methods, recent results, and future directions Bulletin of Mathematical Biology 62 2000 247 292
64. R. Staden Computer methods to locate signals in nucleic acid sequences Nucleic Acids Research 12 1984 505 519
65. G. Stormo DNA binding sites: Representation and discovery Bioinformatics 16 2000 16 23
66. G.D. Stormo, T.D. Schneider, L. Gold, and A. Ehrenfeucht Use of the Perceptron algorithm to distinguish translational initiation sites in E. coli Nucleic Acids Research 10 1982 2997 3012
67. J. Tegner, M.K.S. Yeung, J. Hasty, and J.J. Collins Reverse engineering gene networks: Integrating genetic perturbations with dynamical modeling PNAS 100 2003 5944 5949
68. D. Thieffry, A.M. Huerta, E. Perez-Rueda, and J. Collado-Vides From specific gene regulation to genomic networks: A global analysis of transcriptional regulation in Escherichia coli BioEssays 20 1998 433 440
69. J.D. Thompson, D.G. Higgins, and T.J. Gibson CLUSTAL W: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice Nucleic Acids Research 22 1994 4673 4680
70. L.F.A. van Someren, Wessels, E. Backer, and M.J.T. Reinders Multi-criterion optimization for genetic network modeling Signal Processing 83 2003 763 775
71. G. von Dassow, E. Meir, E.M. Munro, and G.M. Odell The segment polarity network is a robust developmental module Nature 406 2000 188 192
72. A. Wagner Estimating coarse gene network structure from large-scale gene perturbation data Genome Research 12 2002 309 315
73. L. Wang, Q. Wu, P. Qiu, A. Mirza, M. McGuirk, P. Kirschmeier, J.R. Greene, Y. Wang, C.B. Pickett, and S. Liu Analyses of p53 target genes in the human genome by bioinformatic and microarray approaches Journal of Biological Chemistry 276 2001 43604 43610
74. W.W. Wasserman, M. Palumbo, W. Thompson, J.W. Fickett, and C.E. Lawrence Human-mouse genome comparisons to locate regulatory sites Nature Genetics 26 2000 225 228
75. E. Wingender, X. Chen, R. Hehl, H. Karas, I. Liebich, V. Matys, T. Meinhardt, M. Pruss, I. Reuter, and F. Schacherer TRANSFAC: An integrated system for gene expression regulation Nucleic Acids Research 28 2000 316 319
76. M.K.S. Yeung, J. Tegner, and J.J. Collins Reverse engineering gene networks using singular value decomposition and robust regression PNAS 99 2002 6163 6168
77. X. Zhou, X. Wang, and E.R. Dougherty Construction of genomic networks using mutual-information clustering and reversible-jump Markov-chain-Monte-Carlo predictor design Signal Processing 83 2003 745 761