A systems approach to integrative biology: An overview of statistical methods to elucidate association and architecture

Integrative and Comparative Biology

Volumn 54, Issue 2, 2014, Pages 296-306

  Ciaccio, Mark F ^a   Finkle, Justin D ^b   Xue, Albert Y ^a   Bagheri, Neda ^a,b  

^a Northwestern University   (United States)

^b NORTHWESTERN UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANIMAL; BIOLOGICAL MODEL; GENOMICS; MYTILUS; PHYSIOLOGY; PROCEDURES; PROTEOMICS; SIGNAL TRANSDUCTION; SYSTEMS BIOLOGY; TEMPERATURE;

ANIMALS; GENOMICS; MODELS, BIOLOGICAL; MYTILUS; PROTEOMICS; SIGNAL TRANSDUCTION; SYSTEMS BIOLOGY; TEMPERATURE;

EID: 84904635670     PISSN: 15407063     EISSN: 15577023     Source Type: Journal    
DOI: 10.1093/icb/icu037     Document Type: Conference Paper

References (40)

1. Bagheri N, Shiina M, Lauffenburger DA, Korn WM. 2011. A dynamical systems model for combinatorial cancer therapy enhances oncolytic adenovirus efficacy by MEK-inhibition. PLoS Comput Biol 7:e1001085.
2. Bagheri N, Stelling J, Doyle FJ. 2007. Circadian phase entrainment via nonlinear model predictive control. Int J Robust Nonlinear Control 17:1555-71.
3. Bhalla US, Iyengar R. 1999. Emergent properties of networks of biological signaling pathways. Science 283:381-7.
4. Braby CE, Somero GN. 2006. Ecological gradients and relative abundance of native (Mytilus trossulus) and invasive (Mytilus galloprovincialis) blue mussels in the california hybrid zone. Marine Biol 148:1249-62.
5. Braby CE, Somero GN. 2006. Following the heart: Temperature and salinity effects on heart rate in native and invasive species of blue mussels (genus Mytilus). J Exp Biol 209:2554-66.
6. Ciaccio MF, Wagner JP, Chuu C, Lauffenburger DA, Jones RB. 2010. Systems analysis of EGF receptor signaling dynamics with microwestern arrays. Nat Methods 7:148-55.
7. Cho S, Kim K, Kim YJ, Lee J, Cho YS, Lee J, Han B, Kim H, Ott J, Park T. 2010. Joint identification of multiple genetic variants via elastic-net variable selection in a genome-wide association analysis. Ann Hum Genet 74:416-28.
8. Cowan NJ, Ankarali MM, Dyhr JP, Madhav MS, Roth E, Sefati S, Sponberg S, Stamper S, Fortune ES, Daniel TL. 2014. Feedback control as a framework for understanding tradeoffs in biology. Integr Comp Biol 54:223-37.
9. Dalle-Donne I, Rossi R, Milzani A, Di Simplicio P, Colombo R. 2001. The actin cytoskeleton response to oxidants: From small heat shock protein phosphorylation to changes in the redox state of actin itself. Free Radic Biol Med 31:1624-32.
10. Ferreira L, Hitchcock DB. 2009. A comparison of hierarchical methods for clustering functional data. Commun Stat Simul Comput 38:1925-49.
11. Funtowicz S, Ravetz JR. 1994. Emergent complex systems. Futures 26:568-82.
12. Gosling E. 1992. The mussel Mytilus: Ecology, physiology, genetics and culture. 1st ed. Elsevier.
13. Haury A, Mordelet F, Vera-Licona P, Vert J. 2012. TIGRESS: Trustful inference of gene regulation using stability selection. BMC Syst Biol 6:145.
14. Hawkins DM, Basak SC, Mills D. 2003. Assessing model fit by cross-validation. J Chem Inform Comput Sci 43:579-86.
15. Hecker M, Lambeck S, Toepfer S, Someren EV, Guthke R. 2009. Gene regulatory network inference: Data integration in dynamic models, a review. Biosystems 96:86-103.
16. Hoerl AE, Kennard RW. 1970. Ridge regression: Biased estimation for nonorthogonal problems. Technometrics 12:55-67.
17. Holiday DB, Ballard JE, McKeown BC. 1995. Press-related statistics: Regression tools for cross-validation and case diagnostics. Med Sci Sports Exerc 27:612-20.
18. Irrthum A, Wehenkel L, Geurts P. 2010. Inferring regulatory networks from expression data using tree-based methods. PLoS One 5:e12776.
19. James G, Witten D, Hasti T. 2013. An introduction to statistical learning with applications in R. 1st ed. New York: Springer.
20. Janes KA, Kelly JR, Gaudet S, Albeck JG, Sorger PK, Lauffenburger LA. 2004. Cue-signal-response analysis of TNF-induced apoptosis by partial least squares regression of dynamic multivariate data. J Comput Biol 11:544-62.
21. Jong HD. 2002. Modeling and simulation of genetic regulatory systems: A literature review. J Comput Biol 9:67-103.
22. Marbach D, Costello JC, Küffner R, Vega NM, Prill RJ, Camacho DM, Allison KR, The DREAM5
23. ConsortiumKellis M, Collins JJ, Stolovitzky G. 2012. Wisdom of crowds for robust gene network inference. Nat Methods 9:796-804.
24. Margolin AA, Nemenman I, Basso K, Wiggins C, Stolovitzky G, Favera RD, Califano A. 2006. ARACNE: An algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformat 7(Suppl. 1):S7.
25. Meyer C. 2000. Matrix analysis and applied linear algebra book and solutions manual. 2nd ed. SIAM.
26. Murphy KP. 2012. Machine learning: A probabilistic perspective. 1st ed. Cambridge: The MIT Press.
27. Myers RH. 1990. Classical and modern regression with applications. 2nd ed. Belmont: Duxbury Press.
28. Purvis JE, KarhohsKW,Mock C, Batchelor E, Loewer A, Lahav G. 2012. p53 dynamics control cell fate. Science 336:1440-4.
29. Sachs K, Perez O, Pe'er D, Lauffenburger DA, Nolan GP. 2005. Causal protein-signaling networks derived from multiparameter single-cell data. Science 308:523-9.
30. Smith LI. 2002. A tutorial on principal components analysis. New York: Cornell University.
31. Strang G. 2003. Introduction to linear algebra. 4th ed. Wellesley (MA): Wellesley Cambridge Press.
32. Stuart JM, Segal E, Koller D, Kim SK. 2003. A gene-coexpression network for global discovery of conserved genetic modules. Science 302:249-55.
33. Tibshirani R. 1997. The lasso method for variable selection in the Cox model. Stat Med 16:385-95.
34. Tomanek L, Zuzow MJ. 2010. The proteomic response of the mussel congeners Mytilus galloprovincialis and M. trossulus to acute heat stress: Implications for thermal tolerance limits and metabolic costs of thermal stress. J Exp Biol 213:3559-74.
35. Tong AHY, Lesage G, Bader GD, Ding H, Xu H, Xin X, Young J, Berriz GF, Brost RL, Chang M, et al. 2004. Global mapping of the yeast genetic interaction network. Science 303:808-13.
36. Ward JH Jr. 1963. Hierarchical grouping to optimize an objective function. J Am Stat Assoc 58:236-44.
37. Winemiller KO. 1990. Spatial and temporal variation in tropical fish trophic networks. Ecol Monogr 60:331-67.
38. Yu J, Smith VA, Wang PP, Hartemink AJ, Jarvis ED. 2004. Advances to Bayesian network inference for generating causal networks from observational biological data. Bioinformatics 20:3594-603.
39. Zheng Y, Zhang C, Croucher DR, Soliman MA, St-Denis N, Pasculescu A, Taylor L, Tate SA, Hardy WR, Colwill K, et al. 2013. Temporal regulation of EGF signalling networks by the scaffold protein Shc1. Nature 499:166-71.
40. Zou H, Hastie T. 2003. Regression shrinkage and selection via the elastic net, with applications to microarrays. J R Stat Soc Ser B 67:301-20.