Introduction to Systems Biology for Animal Scientists

Systems Biology and Livestock Science

Volumn , Issue , 2011, Pages 1-30

  Tuggle, Christopher K ^a   Towfic, Fadi ^a   Honavar, Vasant G ^a  

^a IOWA STATE UNIVERSITY   (United States)

Author keywords

Animal science; Immunogenomics; Network modeling; Systems biology; Transcriptomics

Indexed keywords

EID: 84872813367     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9780470963012.ch1     Document Type: Chapter

References (168)

1. Abba,M.C., Drake, J.A., Hawkins, K.A., et al. (2004) Transcriptomic changes in human breast cancer progression as determined by serial analysis of gene expression. Breast Cancer Research 6, R499-R513.
2. Adjaye, J. (2005) Whole-genome approaches for large-scale gene identification and expression analysis in mammalian preimplantation embryos. Reproduction, Fertility and Development 17, 37-45.
3. Ahmad, I., Acharya, H.R., Rogers, J.A., et al. (1998) The role of NeuroD as a differentiation factor in the mammalian retina. Journal of Molecular Neuroscience 11, 165-178.
4. Akimoto, M., Cheng, H., Zhu, D., et al. (2006) Targeting of GFP to newborn rods by Nrl promoter and temporal expression profiling of flow-sorted photoreceptors. Proceedings of the National Acadademy of Sciences of the USA 103, 3890-3895.
5. Alon, U., Barkai, N., Notterman, D.A., et al. (1999) Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. Proceedings of the National Acadademy of Sciences of the USA 96, 6745-6750.
6. Amit, I., Garber, M., Chevrier, N., et al. (2009) Unbiased reconstruction of a mammalian transcriptional network mediating pathogen responses. Science 326(5950), 257-263.
7. Auffray, C., Imbeaud, S., Roux-Rouquie,M., et al. (2003) From functional genomics to systems biology: concepts and practices. Comptes Rendus Biologies 326, 879-892.
8. Bader, G.D., Betel, D., & Hogue, C.W. (2003) BIND: the Biomolecular Interaction Network Database. Nucleic Acids Research 31, 248-250.
9. Bader, J.S. (2003) Greedily building protein networks with confidence. Bioinformatics 19, 1869-1874.
10. Bader, J.S., Chaudhuri, A., Rothberg, J.M., et al. (2004) Gaining confidence in high-throughput protein interaction networks. Nature Biotechnology 22, 78-85.
11. Baitaluk, M., Qian, X., Godbole, S., et al. (2006) PathSys: integrating molecular interaction graphs for systems biology. BMC Bioinformatics 7, 55.
12. Bangs, F., Welten, M., Davey, M.G., et al. (2010) Identification of genes downstream of the Shh signalling in the developing chick wing and syn-expressed with Hoxd13 using microarray and 3D computational analysis. Mechanisms of Development 127, 428-441.
13. Bar-Joseph, Z. (2004) Analyzing time series gene expression data. Bioinformatics 20, 2493- 2503.
14. Basso, K., Margolin, A.A., Stolovitzky, G., et al. (2005) Reverse engineering of regulatory networks in human B cells. Nature Genetics 37, 382-390.
15. Bendixen, E., Danielsen, M., Larsen, K., et al. (2010) Advances in porcine genomics and proteomics-a toolbox for developing the pig as a model organism for molecular biomedical research. Briefings in Functional Genomics 9, 208-219.
16. Berg, J., Lassig, M., & Wagner, A. (2004) Structure and evolution of protein interaction networks: a statistical model for link dynamics and gene duplications. BMC Evolutionary Biology 4, 51.
17. Bernard, A. & Hartemink, A.J. (2005) Informative structure priors: joint learning of dynamic regulatory networks from multiple types of data. Pacific Symposium on Biocomputing, 459-470.
18. Blackshaw, S., Harpavat, S., Trimarchi, J., et al. (2004) Genomic analysis of mouse retinal development. PLoS Biology 2, E247.
19. Breitkreutz, B.J., Stark, C., & Tyers, M. (2003) The GRID: the General Repository for Interaction Datasets. Genome Biology 4, R23.
20. Brown, M.P., Grundy,W.N., Lin, D., et al. (2000) Knowledge-based analysis ofmicroarray gene expression data by using support vector machines. Proceedings of the National Academy of Sciences of the USA 97, 262-267.
21. Bruggeman, F.J. & Westerhoff, H.V. (2007) The nature of systems biology. Trends in Microbiology 15, 45-50.
22. Burt, D.W. (2005) Chicken genome: current status and future opportunities. Genome Research 15, 1692-1698.
23. Burt, D.W. (2007) Emergence of the chicken as a model organism: implications for agriculture and biology. Poultry Science 86, 1460-1471.
24. Carter, S.L., Brechbuhler, C.M., Griffin, M., et al. (2004) Gene co-expression network topology provides a framework for molecular characterization of cellular state. Bioinformatics 20, 2242-2250.
25. Chatr-aryamontri, A., Ceol, A., Palazzi, L.M., et al. (2007) MINT: the Molecular Interaction database. Nucleic Acids Research 35(Database issue), D572-D574.
26. Chen, K.C., Wang, T.Y., Tseng, H.H., et al. (2005) A stochastic differential equation model for quantifying transcriptional regulatory network in Saccharomyces cerevisiae. Bioinformatics 21, 2883-2890.
27. Chen, S., Wang, Q.L., Nie, Z., et al. (1997) Crx, a novel Otx-like paired-homeodomain protein, binds to and transactivates photoreceptor cell-specific genes. Neuron 19, 1017-1030.
28. Cheng, H., Khanna, H., Oh, E.C., et al. (2004) Photoreceptor-specific nuclear receptor NR2E3 functions as a transcriptional activator in rod photoreceptors. HumanMolecular Genetics 13, 1563-1575.
29. Churchill, G.A. (2002) Fundamentals of experimental design for cDNA microarrays. Nature Genetics 32(Suppl), 490-495.
30. Cogburn, L.A., Porter, T.E., Duclos, M.J., et al. (2007) Functional genomics of the chicken-a model organism. Poultry Science 86, 2059-2094.
31. Cole, S.W., Yan,W., Galic, Z., et al. (2005) Expression-basedmonitoring of transcription factor activity: the TELiS database. Bioinformatics 21, 803-810.
32. Conrad,E.&Tyson, J. (2006) Modeling molecular interaction networks with nonlinear ordinary differential equations. In: System Modeling in Cellular Biology (Eds. Z. Szallasi, J. Stelling, & V. Periwal), pp. 97-124. MIT Press, Cambridge, MA, USA.
33. Dalloul, R.A., Long, J.A., Zimin, A.V., et al. (2010) Multi-platform next-generation sequencing of the domestic turkey (Meleagris gallopavo): genome assembly and analysis. PLoS Biology 8(9), pii: e1000475.
34. Datta, A., Choudhary, A., Bittner, M.L., et al. (2004) External control in Markovian genetic regulatory networks: the imperfect information case. Bioinformatics 20, 924-930.
35. Davey, M.G., Paton, I.R., Yin, Y., et al. (2006) The chicken talpid3 gene encodes a novel protein essential for Hedgehog signaling. Genes & Development 20, 1365-1377.
36. de Jong, H. (2002) Modeling and simulation of genetic regulatory systems: a literature review. Journal of Computational Biology 9, 67-103.
37. de Koning, D.J., Carlborg, O., & Haley, C.S. (2005) The genetic dissection of immune response using gene-expression studies and genome mapping. Veterinary Immunology and Immunopathology 105, 343-352.
38. de Koning, D.J. & Haley, C.S. (2005) Genetical genomics in humans and model organisms. Trends in Genetics 21, 377-381.
39. Dehoux J.P. & Gianello P. (2007) The importance of large animal models in transplantation. Frontiers in Bioscience 12, 4864-4880.
40. Dekkers J.C. & Hospital F. (2002) The use of molecular genetics in the improvement of agricultural populations. Nature Reviews Genetics 3, 22-32.
41. Del Vecchio, D. & Sontag, E.D. (2007) Dynamics and control of synthetic bio-molecular networks. In: American Control Conference, pp. 1577-1588. New York. Available on: http://www.mit.edu/~esontag/PUBDIR/Category/conferences.html.
42. Dhillon, I.S., Guan, Y.,&Kulis,B. (2007) Weighted graph cutswithout eigenvectors a multilevel approach. IEEE Transactions on Pattern Analysis and Machine Intelligence 29, 1944-1957.
43. Ding, C., He, X., & Simon, H.D. (2005) On the Equivalence of Nonnegative Matrix Factorization and Spectral Clustering. pp. 606-610. In: Proceedings SIAM Data Mining Conf, Society for Industrial and Applied Mathematics, Philadelphia, USA.
44. Dorrell, M.I., Aguilar, E., Weber, C., et al. (2004) Global gene expression analysis of the developing postnatal mouse retina. Investigative Ophthalmology & Visual Sciece 45, 1009- 1019.
45. Dow, J.A. (2007) Integrative physiology, functional genomics and the phenotype gap: a guide for comparative physiologists. Journal of Experimental Biology 210(Pt 9), 1632-1640.
46. Edwards, A.M., Kus, B., Jansen, R., et al. (2002) Bridging structural biology and genomics: assessing protein interaction data with known complexes. Trends in Genetics 18, 529-536.
47. Eisen, M.B., Spellman, P.T., Brown, P.O., et al. (1998) Cluster analysis and display of genomewide expression patterns. Proceedings of the National Acadademy of Sciences of the USA 95, 14863-14868.
48. Farkas, I., Jeong, H., Vicsek, T., et al. (2003) The topology of the transcription regulatory network in the yeast, Saccharomyces cerevisiae. Physica A: Statistical Mechanics and its Applications, Elsevier 318, 601-612.
49. Fazeli, A. (2008) Maternal communication with gametes and embryos. Theriogenology 70, 1182-1187.
50. Fazeli, A. & Pewsey, E. (2008) Maternal communication with gametes and embryos: a complex interactome. Briefings in Functional Genomics and Proteomics 7, 111-118.
51. Fraser, C.M., Rider, L.W., & Chapple, C. (2005) An expression and bioinformatics analysis of the Arabidopsis serine carboxypeptidase-like gene family. Plant Physiology 138, 1136-1148.
52. Friedman, N., Linial, M., Nachman, I., et al. (2000) Using Bayesian networks to analyze expression data. Journal of Computational Biology 7, 601-620.
53. Gardy, J.L., Lynn, D.J., Brinkman, F.S., et al. (2009) Enabling a systems biology approach to immunology: focus on innate immunity. Trends in Immunology 30, 249-262.
54. Garey, M.R. & Johnson, D.S. (1990) Computers and Intractability: A Guide to the Theory of NP-Completeness. W.H. Freeman & Co, New York, USA.
55. Gavin, A.C., Bosche,M., Krause, R., et al. (2002) Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature, 415(6868), 141-147.
56. Ge, H., Walhout, A.J., & Vidal, M. (2003) Integrating 'omic' information: a bridge between genomics and systems biology. Trends in Genetics 19, 551-560.
57. Georges, M. (2007) Mapping, fine mapping, and molecular dissection of quantitative trait loci in domestic animals. Annual Review of Genomics and Human Genetics 8, 131-162.
58. Ghahramani, Z. (1998) Learning Dynamic Bayesian Networks, Lecture Notes in Artificial Intelligence, pp. 168-197. Springer-Verlag, Berlin, Germany.
59. Gilchrist, M., Thorsson, V., Li, B., et al. (2006) Systems biology approaches identify ATF3 as a negative regulator of Toll-like receptor 4. Nature 441(7090), 173-178.
60. Green, E.S., Stubbs, J.L., & Levine, E.M. (2003) Genetic rescue of cell number in a mouse model of microphthalmia: interactions between Chx10 and G1-phase cell cycle regulators. Development 130, 539-552.
61. Green, R.D. (2009) ASAS centennial paper: Future needs in animal breeding and genetics. Journal of Animal Science 87, 793-800.
62. Green, R.D., Qureshi, M.A., Long, J.A., et al. (2007) Identifying the future needs for long-term USDA efforts in agricultural animal genomics. International Journal of Biological Science 3, 185-191.
63. Han, J.D., Bertin, N., Hao, T., et al. (2004) Evidence for dynamically organized modularity in the yeast protein-protein interaction network. Nature, 430(6995), 88-93.
64. Hartemink, A.J., Gifford, D., Jaakkola, T., et al. (2002) Bayesian Methods for Elucidating Genetic Regulatory Networks. IEEE Intelligent Systems 17, 37-43.
65. Hecker, L.A., Alcon, T.A., Honavar, v., et al. (2008) Using a Seed-Network to Query Multiple Large-Scale Gene Expression Datasets from the Developing Retina in Order to Identify and Prioritize Experimental Targets. Bioinformatics and Biology Insights 2, 91-102.
66. Heng, T.S. & Painter, M.W. (2008) The Immunological Genome Project: networks of gene expression in immune cells. Nature Immunology 9, 1091-1094.
67. Ho Sui, S.J., Fulton, D.L., Arenillas, D.J., et al. (2007) oPOSSUM: integrated tools for analysis of regulatory motif over-representation. Nucleic Acids Research 35(Web Server issue), W245-W252.
68. Ho, Y., Gruhler, A., Heilbut, A., et al. (2002) Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature, 415(6868), 180-183.
69. Hornshoj, H., Bendixen, E., Conley, L.N., et al. (2009) Transcriptomic and proteomic profiling of two porcine tissues using high-throughput technologies. BMC Genomics, 10, 30.
70. Hu, X., Gao, Y., Feng, C., et al. (2009) Advanced technologies for genomic analysis in farm animals and its application for QTL mapping. Genetica 136, 371-386.
71. Hudson, N.J., Reverter, A.,&Dalrymple,B.P. (2009)Adifferentialwiring analysis of expression data correctly identifies the gene containing the causalmutation. PLoS ComputationalBiology 5, e1000382.
72. Hyatt, G., Melamed, R., Park, R., et al. (2006) Gene expression microarrays: glimpses of the immunological genome. Nature Immunology 7, 686-691.
73. ICGSC (2004) Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution. Nature, 432(7018), 695-716.
74. Ideker, T. (2004) Systems biology 101-what you need to know. Nature Biotechnology 22, 473- 475.
75. IHGSC (2004) Finishing the euchromatic sequence of the human genome. Nature, 431(7011), 931-945.
76. Ihmels, J., Friedlander, G., Bergmann, S., et al. (2002) Revealing modular organization in the yeast transcriptional network. Nature Genetics 31, 370-377.
77. Ito, T., Chiba, T., Ozawa, R., et al. (2001) A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proceedings of the National Acaddemy of Science of the USA, 98, 4569-4574.
78. Ito, T., Tashiro, K., Muta, S., et al. (2000) Toward a protein-protein interaction map of the budding yeast: a comprehensive system to examine two-hybrid interactions in all possible combinations between the yeast proteins. Proceedings of the National Acaddemy of Science of the USA, 97, 1143-1147.
79. Jeong, H., Mason, S.P., Barabasi, A.L., et al. (2001) Lethality and centrality in protein networks. Nature, 411(6833), 41-42.
80. Jeong, H., Tombor, B., Albert, R., et al. (2000) The large-scale organization of metabolic networks. Nature, 407(6804), 651-654.
81. Jiang, D., Tang, C., & Zhang, A. (2004) Cluster Analysis for Gene Expression Data: A Survey. IEEE Transactions on Knowledge and Data Engineering (TKDE) 22, 1370-1386.
82. Jupiter, D., Chen, H., & VanBuren, V. (2009) STARNET 2: a web-based tool for accelerating discovery of gene regulatory networks using microarray co-expression data. BMC Bioinformatics, 10, 332.
83. Kadarmideen, H.N. & Janss, L.L. (2007) Population and systems genetics analyses of cortisol in pigs divergently selected for stress. Physiological Genomics 29, 57-65.
84. Kambadur, R., Sharma, M., Smith, T.P., et al. (1997) Mutations in myostatin (GDF8) in doublemuscled Belgian Blue and Piedmontese cattle. Genome Research 7, 910-916.
85. Kanehisa, M., Araki, M., Goto, S., et al. (2008) KEGG for linking genomes to life and the environment. Nucleic Acids Research 36(Database issue), D480-D484.
86. Kassab, G.S. (2009) A systems approach to tissue remodeling. Journal of Biomechanical Engineering 131, 101008.
87. Kauffman, S.A. (1993) The origins of order: self-organization and selection in evolution. Oxford University Press, New York, USA.
88. Khanin, R. & Wit, E. (2006) How scale-free are biological networks. Journal of Computational Biology 13, 810-818.
89. Kim, H., Lee, J.K., & Park, T. (2007) Boolean networks using the chi-square test for inferring large-scale gene regulatory networks. BMC Bioinformatics 8, 37.
90. Kitano, H. (2002) Systems biology: a brief overview. Science 295(5560), 1662-1664.
91. Kleinstein, S.H. (2008) Getting started in computational immunology. PLoS Computational Biology 4, e1000128.
92. Klipp, E., Herwig, R., Kowald, A., et al. (2005) Systems Biology in Practice. Wiley-VCH, Weinheim, Germany.
93. Kohutyuk, O. (2007) Retina Workbench: A Flexible Database System for Manipulating and Mining Expression Data and Genetic Regulatory Networks. In: Computer Science, pp. (In preparation). Iowa State University, Ames, IA, USA.
94. Kolbehdari, D., Wang, Z., Grant, J.R., et al. (2009) A whole genome scan to map QTL for milk production traits and somatic cell score in Canadian Holstein bulls. Journal of Animal Breeding and Genetics 126, 216-227.
95. Konieczka, J.H., Drew, K., Pine, A., et al. (2009) BioNetBuilder2.0: bringing systems biology to chicken and other model organisms. BMC Genomics 10(Suppl 2), S6.
96. Krogan, N.J., Peng,W.T., Cagney,G., et al. (2004) High-definition macromolecular composition of yeast RNA-processing complexes. Molecular Cell 13, 225-239.
97. Krull, M., Pistor, S., Voss, N., et al. (2006) TRANSPATH: an information resource for storing and visualizing signaling pathways and their pathological aberrations. Nucleic Acids Research, 34(Database issue), D546-D551.
98. L¨ahdesm¨aki, H.,Hautaniemi, S., Shmulevich, I., et al. (2006) Relationships between probabilistic Boolean networks and dynamic Bayesian networks as models of gene regulatory networks. Signal Processing 86, 814-834.
99. L¨ahdesm¨aki, H. & Shmulevich, I. (2008) Learning the structure of dynamic Bayesian networks from time series and steady state measurements. Machine Learning, Springer 71, 185- 217.
100. Lahdesmaki, H., Shmulevich, I., & O., Y.-H. (2003) On learning gene regulatory networks under the boolean network model. Machine Learnings 52, 147-167.
101. Lamont, S.J. (2006) Perspectives in chicken genetics and genomics. Poultry Science 85, 2048-2049.
102. Lander, E.S., Linton, L.M., Birren, B., et al. (2001) Initial sequencing and analysis of the human genome. Nature 409(6822), 860-921.
103. Litvak, V., Ramsey, S.A., Rust, A.G., et al. (2009) Function of C/EBPdelta in a regulatory circuit that discriminates between transient and persistent TLR4-induced signals. Nature Immunology 10, 437-443.
104. Liu, E.T. (2005) Systems biology, integrative biology, predictive biology. Cell 121, 505-506.
105. Liu, J.,Wang, J., Huang, Q., et al. (2006) Gene expression profiles of mouse retinas during the second and third postnatal weeks. Brain Research 1098, 113-125.
106. Liu, R. & Agarwal, P. (2005) Computational identification of transcription factors involved in early cellular response to a stimulus. Journal of Bioinformatics and Computational Biology 3, 949-964.
107. Loosky, P.M., Zhang, X., Honavar, V.G., et al. (2004) A proteomic analysis of maize chloroplast biogenesis. Plant Physiology 134, 560-574.
108. Loor, J.J. & Cohick, W.S. (2009) ASAS centennial paper: Lactation biology for the twenty-first century. Journal of Animal Science 87, 813-824.
109. Lunney, J.K. (2007) Advances in swine biomedical model genomics. International Journal of Biological Sciences 3, 179-184.
110. Matthews, L.R., Vaglio, P., Reboul, J., et al. (2001) Identification of potential interaction networks using sequence-based searches for conserved protein-protein interactions or " interologs" . Genome Research 11, 2120-2126.
111. McCarthy, F.M., Bridges, S.M., Wang, N., et al. (2007) AgBase: a unified resource for functional analysis in agriculture. Nucleic Acids Research 35(Database issue), D599-D603.
112. Mears, A.J., Kondo, M., Swain, P.K., et al. (2001) Nrl is required for rod photoreceptor development. Nature Genetics 29, 447-452.
113. Milo, R., Shen-Orr, S., Itzkovitz, S., et al. (2002) Network motifs: simple building blocks of complex networks. Science 298(5594), 824-827.
114. Miracle, A.L. & Ankley, G.T. (2005) Ecotoxicogenomics: linkages between exposure and effects in assessing risks of aquatic contaminants to fish. Reproductive Toxicology 19, 321- 326.
115. Mishra, G.R., Suresh, M., Kumaran, K., et al. (2006) Human protein reference database-2006 update. Nucleic Acids Research 34(Database issue), D411-D414.
116. Murali, D., Yoshikawa, S., Corrigan, R.R., et al. (2005) Distinct developmental programs require different levels of Bmp signaling during mouse retinal development. Development 132, 913-923.
117. Myers, C.L. & Troyanskaya, O.G. (2007) Context-sensitive data integration and prediction of biological networks. Bioinformatics 23, 2322-2330.
118. Nilsson, R., Schultz, I.J., Pierce, E.L., et al. (2009) Discovery of genes essential for heme biosynthesis through large-scale gene expression analysis. Cell Metabolism 10, 119-130.
119. Nishida, A., Furukawa, A., Koike, C., et al. (2003) Otx2 homeobox gene controls retinal photoreceptor cell fate and pineal gland development. Nature Neuroscience 6, 1255- 1263.
120. Novak, J.P., Sladek, R., & Hudson, T.J. (2002) Characterization of variability in large-scale gene expression data: implications for study design. Genomics 79, 104-113.
121. Ogata, H., Audic, S., Barbe, V., et al. (2000) Selfish DNA in protein-coding genes of Rickettsia. Science 290(5490), 347-350.
122. Panagiotou G. & Nielsen J. (2009) Nutritional systems biology: definitions and approaches. Annual Review of Nutrition 29, 329-339.
123. Pe'er, D. (2005) Bayesian network analysis of signaling networks: a primer. Science signaling Signal Transduction Knowledge Environment 281, pl4.
124. Pennesi, M.E., Cho, J.H., Yang, Z., et al. (2003) BETA2/NeuroD1 null mice: a new model for transcription factor-dependent photoreceptor degeneration. Journal of Neuroscience 23, 453-461.
125. Picard, B., Berri, C., Lefaucheur, L., et al. (2010) Skeletal muscle proteomics in livestock production. Briefings in Functional Genomics 9, 259-278.
126. Pomp, D., Allan, M.F., & Wesolowski, S.R. (2004) Quantitative genomics: exploring the genetic architecture of complex trait predisposition. Journal of Animal Science 82(E-Suppl), E300-E312.
127. Popovic, N., Bridenbaugh, E.A., Neiger, J.D., et al. (2009) Transforming growth factor-beta signaling in hypertensive remodeling of porcine aorta. American Journal of Physiology - Heart and Circulatory Physiology 297, H2044-H2053.
128. Rajasingh, H., Oyehaug, L., Vage, D.I., et al. (2006) Carotenoid dynamics in Atlantic salmon. BMC Biology 4, 10.
129. Ravasz, E. & Barabasi, A.L. (2003) Hierarchical organization in complex networks. Physical
130. Review E: Statistical, Nonlinear, and Soft Matter Physics 67(2 Pt 2), 026112.
131. Ravasz, E., Somera, A.L., Mongru, D.A., et al. (2002) Hierarchical organization of modularity in metabolic networks. Science 297(5586), 1551-1555.
132. Reverter, A., Hudson, N.J., Nagaraj, S.H., et al. (2010) Regulatory impact factors: unraveling the transcriptional regulation of complex traits from expression data. Bioinformatics 26, 896-904.
133. Rockman, M.V. & Kruglyak, L. (2006) Genetics of global gene expression. Nature Reviews Genetics 7, 862-872.
134. Rutherford, A.D., Dhomen, N., Smith, H.K., et al. (2004) Delayed expression of the Crx gene and photoreceptor development in the Chx10-deficient retina. Investigative Ophthalmology & Visual Science 45, 375-384.
135. Sachs, K., Gifford, D., Jaakkola, T., et al. (2002) Bayesian network approach to cell signaling pathway modeling. Science signaling Signal Transduction Knowledge Environment 148, pe38.
136. Salwinski, L., Miller, C.S., Smith, A.J., et al. (2004) The Database of Interacting Proteins: 2004 update. Nucleic Acids Research 32(Database issue), D449-D451.
137. Scheerlinck, J.P., Snibson, K.J., Bowles, V.M., et al. (2008) Biomedical applications of sheep models: from asthma to vaccines. Trends Biotechnol 26(5): 259-266.
138. Schena, M., Shalon, D., Davis, R.W., et al. (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270(5235), 467-470.
139. Scott, J., Ideker, T., Karp, R.M., et al. (2006) Efficient algorithms for detecting signaling pathways in protein interaction networks. Journal of Computational Biology 13, 133-144.
140. Segal, E., Shapira, M., Regev, A., et al. (2003) Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data. Nature Genetics 34, 166-176.
141. Sellner, E.M., Kim, J.W., McClure, M.C., et al. (2007) Board-invited review: Applications of genomic information in livestock. Journal of Animal Science 85, 3148-3158.
142. Sen, T.Z., Kloczkowski, A., & Jernigan, R.L. (2006) Functional clustering of yeast proteins from the protein-protein interaction network. BMC Bioinformatics 7, 355.
143. Seo, S. & Lewin, H.A. (2009) Reconstruction of metabolic pathways for the cattle genome. BMC Systems Biology 3, 33.
144. Shannon, P., Markiel, A., Ozier, O., et al. (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Research 13, 2498-2504.
145. Sharan, R. & Ideker, T. (2006) Modeling cellular machinery through biological network comparison. Nature Biotechnology 24, 427-433.
146. Shi, J. & Malik, J. (2000) Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 888-905.
147. Shoemaker, J.E., Gayen, K., Garcia-Reyero, N., et al. (2010) Fathead minnow steroidogenesis: in silico analyses reveals tradeoffs between nominal target efficacy and robustness to crosstalk. BMC Systems Biology 4, 89.
148. Sievertzon, M., Wirta, V., Mercer, A., et al. (2005) Transcriptome analysis in primary neural stem cells using a tag cDNA amplification method. BMC Neuroscience 6, 28.
149. Silvescu, A. & Honavar, V. (2001) Temporal boolean network models of genetic networks and their interference from gene expression time series. Complex Systems 13, 54-75.
150. Smith, G.W.&Rosa, G.J. (2007) Interpretation of microarray data: trudging out of the abyss towards elucidation of biological significance. Journal ofAnimal Science 85(13 Suppl),E20-E23.
151. Steibel, J.P., Bates, R.O., Rosa, G.J.M., et al. (2010) Global Linkage Analysis of Gene Expression of Loin Muscle Tissue Identifies Candidate Genes in Pigs. In: 9th World Congress on Genetics Applied to Livestock Production, CD-ROM Communication 0139, Leipzig.
152. Stelzl, U., Worm, U., Lalowski, M., et al. (2005) A human protein-protein interaction network: a resource for annotating the proteome. Cell 122, 957-968.
153. Stuart, J.M., Segal, E., Koller, D., et al. (2003)Agene-coexpression network for global discovery of conserved genetic modules. Science 302(5643), 249-255.
154. Thomas, R. (1973) Boolean formalization of genetic control circuits. Journal of Theoretical Biology 42, 563-585.
155. Tong, A.H., Evangelista,M., Parsons, A.B., et al. (2001) Systematic genetic analysis with ordered arrays of yeast deletion mutants. Science 294(5550), 2364-2368.
156. Towfic, F., VanderPlas, S., Oliver, C.A., et al. (2010) Detection of gene orthology from gene co-expression and protein interaction networks. BMC Bioinformatics 11(Suppl. 3), S7.
157. Tuggle, C.K.,Wang, Y., & Couture, O. (2007) Advances in swine transcriptomics. International Journal of Biological Sciences 3, 132-152.
158. Uetz, P., Giot, L., Cagney, G., et al. (2000) A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae. Nature 403(6770), 623-627.
159. van den Berg, B.H., Konieczka, J.H., McCarthy, F.M., et al. (2009) ArrayIDer: automated structural re-annotation pipeline for DNA microarrays. BMC Bioinformatics 10, 30.
160. von Luxburg, U. (2007) A tutorial on spectral clustering. Statistics and Computing 17, 395-416.
161. Walhout, A.J. (2006) Unraveling transcription regulatory networks by protein-DNA and protein-protein interaction mapping. Genome Research 16, 1445-1454.
162. Wang, Y., Couture, O.P., Qu, L., et al. (2008) Analysis of porcine transcriptional response to Salmonella enterica serovar Choleraesuis suggests novel targets of NFkappaB are activated in the mesenteric lymph node. BMC Genomics 9, 437.
163. Wong, G.K., Liu, B.,Wang, J., et al. (2004) A genetic variation map for chicken with 2. 8 million single-nucleotide polymorphisms. Nature 432(7018), 717-722.
164. Yook, S.H., Oltvai, Z.N., & Barabasi, A.L. (2004) Functional and topological characterization of protein interaction networks. Proteomics 4, 928-942.
165. Yu, H., Zhu, X., Greenbaum, D., et al. (2004a) TopNet: a tool for comparing biological subnetworks, correlating protein properties with topological statistics. Nucleic Acids Research 32, 328-337.
166. Yu, J., He, S., Friedman, J.S., et al. (2004b) Altered expression of genes of the Bmp/Smad and Wnt/calcium signaling pathways in the cone-only Nrl-/- mouse retina, revealed by gene profiling using custom cDNA microarrays. Journal of Biological Chemistry 279, 42211-42220.
167. Zak, D.E. & Aderem, A. (2009) Systems biology of innate immunity. Immunological Reviews 227, 264-282.
168. Zhang, J., Gray, J., Wu, L., et al. (2004) Rb regulates proliferation and rod photoreceptor development in the mouse retina. Nature Genetics 36, 351-360.