A likelihood approach to analysis of network data

Proceedings of the National Academy of Sciences of the United States of America

Volumn 103, Issue 20, 2006, Pages 7566-7570

  Wiuf, Carsten ^a,b   Brameier, Markus ^a   Hagberg, Oskar ^a   Stumpf, Michael P H ^c  

^a AARHUS UNIVERSITY   (Denmark)

^b AARHUS UNIVERSITY HOSPITAL   (Denmark)

^c IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

Biological network; Importance sampling; Likelihood recursion; Network model; Random graph

Indexed keywords

ARTICLE; CAENORHABDITIS ELEGANS; NONHUMAN; PRIORITY JOURNAL; PROTEIN INTERACTION; SAMPLING; STATISTICAL ANALYSIS; STATISTICAL MODEL;

ANIMALS; CAENORHABDITIS ELEGANS; CAENORHABDITIS ELEGANS PROTEINS; DATA INTERPRETATION, STATISTICAL; INFORMATION SERVICES; LIKELIHOOD FUNCTIONS; MATHEMATICS; MODELS, THEORETICAL; NERVE NET; SOCIAL SUPPORT;

CAENORHABDITIS ELEGANS;

EID: 33646745354     PISSN: 00278424     EISSN: None     Source Type: Journal    
DOI: 10.1073/pnas.0600061103     Document Type: Article

References (24)

1. Thompson, C. J. (1979) Mathematical Statistical Mechanics (Princeton Univ. Press, Princeton).
2. Barabási, A. L. & Albert, R. (1999) Science 286, 509-512.
3. Bollobás, B. (2001) Random Graphs (Cambridge Univ. Press, Cambridge, U.K.), 2nd Ed.
4. Dorogovtsev, S. N. & Mendes, J. F. F. (2003) Evolution of Networks: From Biological Nets to the Internet and WWW (Oxford Univ. Press, Oxford).
5. Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskij, D. & Alon, U. (1997) Science 298, 824-827.
6. Chung, F., Linyuan, L., Dewey, G. & Galas, D. (2003) J. Comp. Biol. 10, 677-687.
7. Kumar, S. R., Raghavan, P., Rajagopalan, S., Sivakumar, D., Tomkins, A. & Upfal, E. (2000) in Proceedings of the 41st IEEE Symposium on Foundations of Computer Science, ed. Blum, H. (IEEE Computer Soc., Washington, DC), pp. 57-65.
8. Lauritzen, S. L. (1996) Graphical Models (Clarendon, Oxford).
9. Stumpf, M. P. H., Ingram, P. J., Nouvel, I. & Wiuf, C. (2005) in Transactions in Computational Systems Biology, ed. Priami, C. (Springer, New York), pp. 65-77.
10. Burda, Z., Diaz-Correia, J. & Krzywicki, A. (2001) Phys. Rev. E 64, 046118.
11. Ewens, W. J. (2005) Mathematical Population Genetics (Springer, New York), 2nd Ed.
12. Ripley, B. (1987) Stochastic Simulation (Wiley, Sussex, U.K.).
13. Liu, J. S. (2001) Monte Carlo Strategies in Scientific Computing (Springer, New York).
14. Griffiths, R. C. & Tavaré, S. (1994) Theor. Popul. Biol. 46, 131-159.
15. Griffiths, R. C. & Tavaré, S. (1994) Stat. Sci. 9, 307-319.
16. Griffiths, R. C. & Marjoram, P. (1996) J. Comp. Biol. 3, 479-502.
17. Kingman, J. F. C. (1982) Stoch. Proc. Appl. 13, 235-248.
18. Stephens, M. & Donnelly, P. (2000) J. R. Stat. Soc. B 62, 605-655.
19. Li, S., Armstrong, C. M., Bertin, N., Ge, H., Milstein, S., Boxem, M., Vidalain, P.-O., Han, J.-D. J., Chesneau, A., Hao, T., et al. (2004) Science 303, 540-543.
20. Agrafioti, I., Swire, J., Abbott, J., Huntley, D., Butcher, S. & Stumpf, M. P. H. (2005) BMC Evol. Biol. 5, 23.
21. Lauritzen, S. L. & Richardson, T. S. (2002) J. R. Stat. Soc. B 64, 321-348.
22. Schafer, J. & Strimmer, K. (2005) Bioinformatics 21, 754-764.
23. Pournara, I. & Wernisch, L. (2004) Bioinformatics 20, 2934-2942.
24. Snijders, T. A. B. (2002) J. Soc. Struct. 3, 2.