Biological information as set-based complexity

IEEE Transactions on Information Theory

Volumn 56, Issue 2, 2010, Pages 667-677

  Galas, David J ^a   Nykter, Matti ^a,b   Carter, Gregory W ^a   Price, Nathan D ^a,c   Shmulevich, Ilya ^a  

^a INSTITUTE FOR SYSTEMS BIOLOGY   (United States)

^b TAMPERE UNIVERSITY OF TECHNOLOGY   (Finland)

^c UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

Author keywords

Complexity; Criticality; Information distance; Networks; Set complexity

Indexed keywords

BIOLOGICAL FUNCTIONS; BIOLOGICAL INFORMATION; EBB-AND-FLOW; INFORMATION DISTANCE; KOLMOGOROV; LIVING SYSTEMS; REDUNDANT INFORMATIONS; REPEATED SEQUENCES; STATE SPACE;

COMPUTATIONAL COMPLEXITY; CRITICALITY (NUCLEAR FISSION);

BIOINFORMATICS;

EID: 77649327264     PISSN: 00189448     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIT.2009.2037046     Document Type: Article

References (45)

1. M. S. L. Gell-Mann, "Information measures, effective complexity, and total information," Complexity, vol. 2, no. 1, pp. 44-52, 1996.
2. M. Gell-Mann, The Quark and The Jaguar: Adventures in the Simple and the Complex. New York: Freeman, 1994, p. 392.
3. R. Standish, "On complexity and emergence," Complex. Int., vol. 9, pp. 1-5, 2001.
4. C. Adami and N. J. Cerf, "Physical complexity of symbolic sequences," Phys. D, vol. 137, pp. 62-69, 2000.
5. S. Lloyd and H. Pagels, "Complexity as thermodynamic depth," Ann. Phys., vol. 188, pp. 186-213, 1988.
6. J. P. Crutchfield and C. R. Shalizi, "Thermodynamic depth of causal states: Objective complexity via minimal representations," Phys. Rev. E, vol. 59, no. 1, p. 275, 1999.
7. A. N. Kolmogorov, "Three approaches to the definition of the concept "quantity of information"," (in Russian) Problemy Peredachi Informacii, vol. 1, pp. 3-11, 1965.
8. G. J. Chaitin, "On the length of programs for computing finite binary sequences," J. ACM, vol. 13, no. 4, pp. 547-569, 1966.
9. R. J. Solomonoff, "A formal theory of inductive inference. II," Inf. Contr., vol. 7, pp. 224-254, 1964.
10. R. J. Solomonoff, "A formal theory of inductive inference. I," Inf. Contr., vol. 7, pp. 1-22, 1964.
11. M. Li, C. Xin, L. Xin, M. Bin, and P. M. B. Vitanyi, "The similarity metric," IEEE Trans. Inf. Theory, vol. 50, no. 12, pp. 3250-3264, 2004.
12. P. M. B. Vitanyi and M. Li, "Simplicity, tinformation, Kolmogorov complexity, and prediction," in Simplicity, Inference and Modeling, H. A. K. A. Zellner and M. McAleer, Eds. Cambridge, U.K.: Cambridge University Press, 2002, pp. 135-155.
13. C. H. Bennett, P. Gacs, L. Ming, M. B. Vitanyi, and W. H. Zurek, "Information distance," IEEE Trans. Inf. Theory, vol. 44, no. 4, pp. 1407-1423, 1998.
14. P. Gacs, "The symmetry of algorithmic information," Dokl. Akad. Nauk SSSR, vol. 218, pp. 1265-1267, 1974.
15. C. E. Shannon, "A mathematical theory of communication," Bell Syst. Tech. J., vol. 27, pp. 379-423, 1948.
16. M. Li and P. M. B. Vitânyi, An Introduction to Kolmogorov Complexity and Its Applications, 2nd ed. New York: Springer, 1997, p. 637.
17. R. Cilibrasi and P. M. B. Vitanyi, "Clustering by compression," IEEE Trans. Inf. Theory, vol. 51, no. 4, pp. 1523-1545, 2005.
18. P. Martin-Lof, "The definition of random sequences," Inf. Contr., vol. 9, pp. 602-619, 1966.
19. A. K. Shen, "The notion of (α,β)-stochasticity in Kolmogorov's sense and its properties," Dokl. Akad. Nauk SSSR, vol. 271, no. 6, pp. 1337-1340, 1983.
20. P. D. Grünwald and P. M. B. Vitányi, "Kolmogorov complexity and information theory. With an interpretation in terms of questions and answers," J. Logic, Language Inf., vol. 12, no. 4, pp. 497-529, 2003.
21. P. Gacs, J. T. Tromp, and P. M. B. Vitanyi, "Algorithmic statistics," IEEE Trans. Inf. Theory, vol. 47, pp. 2443-2463, 2001.
22. P. Ferragina, R. Giancarlo, V. Greco, G. Manzini, and G. Valiente, "Compression-based classification of biological sequences and structures via the Universal Similarity Metric: Experimental assessment," BMC Bioinform., vol. 8, p. 252, 2007.
23. S. Kauffman, "Homeostasis and differentiation in random genetic control networks," Nature, vol. 224, no. 215, pp. 177-8, 1969.
24. S. A. Kauffman, The Origins of Order: Self Organization and Selection in Evolution. New York: Oxford University Press, 1993, p. 709.
25. M. Aldana, S. Coppersmith, and L. P. Kadanoff, "Boolean dynamics with random couplings," in Perspectives and Problems in Nonlinear Science, E. Kaplan, J. E. Marsden, and K. R. Sreenivasan, Eds. New York: Springer, 2002, pp. 23-89.
26. R. Albert and H. G. Othmer, "The topology of the regulatory interactions predicts the expression pattern of the segment polarity genes in Drosophila melanogaster," J. Theor. Biol., vol. 223, no. 1, pp. 1-18, 2003.
27. C. Espinosa-Soto, P. Padilla-Longoria, and E. R. Alvarez-Buylla, "A gene regulatory network model for cell-fate determination during Arabidopsis thaliana flower development that is robust and recovers experimental gene expression profiles," Plant Cell, vol. 16, no. 11, pp. 2923-39, 2004.
28. F. Li, T. Long, Y. Lu, Q. Ouyang, and C. Tang, "The yeast cell-cycle network is robustly designed," Proc. Nat. Acad. Sci. USA, vol. 101, no. 14, pp. 4781-4786, 2004.
29. A. Faure, A. Naldi, C. Chaouiya, and D. Thieffry, "Dynamical analysis of a generic Boolean model for the control of the mammalian cell cycle," Bioinform., vol. 22, no. 14, pp. e124-31, 2006.
30. U. Bastolla and G. Parisi, "Relevant elements, magnetization and dynamical properties in Kauffman networks: A numerical study," Phys. D: Nonlin. Phenom., vol. 115, no. 3-4, pp. 203-218, 1998.
31. P. Ramo, J. Kesseli, and O. Yli-Harja, "Perturbation avalanches and criticality in gene regulatory networks," J. Theor. Biol., vol. 242, no. 1, pp. 164-70, 2006.
32. R. Serra, M. Villani, and A. Semeria, "Genetic network models and statistical properties of gene expression data in knock-out experiments," J. Theor. Biol., vol. 227, no. 1, pp. 149-57, 2004.
33. I. Shmulevich, S. A. Kauffman, and M. Aldana, "Eukaryotic cells are dynamically ordered or critical but not chaotic," Proc. Nat. Acad. Sci. USA, vol. 102, no. 38, pp. 13439-13444, 2005.
34. I. Shmulevich and S. A. Kauffman, "Activities and sensitivities in Boolean network models," Phys. Rev. Lett., vol. 93, no. 4, pp. 048701-4, 2004.
35. B. Derrida and Y. Pomeau, "Random networks of automata: A simple annealed approximation," Europhys. Lett., vol. 1, no. 2, pp. 45-49, 1986.
36. B. Luque and R. V. Sole, "Lyapunov exponents in random Boolean networks," Phys. A: Statist. Mechan. Its Applicat., vol. 284, no. 1-4, pp. 33-45, 2000.
37. G. W. Carter, D. J. Galas, and T. Galitski, "Maximal extraction of biological information from genetic interaction data," PLoS Comput. Biol., vol. 5, no. 4, p. e1000347, 2009.
38. N. Tishby, F. C. Pereira, and W. Bialek, "The information bottleneck method," Arxiv Preprint Physics/0004057, 2000.
39. M. J. Smith, "The 1999 Crafoord Prize Lectures. The idea of information in biology," Quart. Rev. Biol., vol. 74, no. 4, pp. 395-400, 1999.
40. M. J. Smith, "The concept of information in biology," Philos. Sci., vol. 67, no. 2, pp. 177-194, 2000.
41. L. Hood and D. Galas, "The digital code of DNA," Nature, vol. 421, no. 6921, pp. 444-8, 2003.
42. L. H. Hartwell, J. J. Hopfield, S. Leibler, and A. W. Murray, "From molecular to modular cell biology," Nature, vol. 402, no. 6761 Suppl, pp. C47-52, 1999.
43. R. A. Barrio, P. K. Maini, J. L. Aragon, and M. Torres, "Size-dependent symmetry breaking in models for morphogenesis," Phys. D: Nonlin. Phenom., vol. 168-169, pp. 61-72, 2002.
44. M. Li, J. Tromp, and P. Vitanyi, "Sharpening Occam's razor," Inf. Processing Lett., vol. 85, no. 5, pp. 267-274, 2003.
45. N. Chater and P. M. B. Vitanyi, "The generalized universal law of generalization," J. Math. Psychol., vol. 47, pp. 346-369, 2003.