How networks change with time

Bioinformatics

Volumn 28, Issue 12, 2012, Pages

  Park, Yongjin ^a,b   Bader, Joel S ^a,b  

^a Johns Hopkins University School of Medicine   (United States)

^b JOHNS HOPKINS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ANIMAL; ARTICLE; BAYES THEOREM; BIOLOGY; CLUSTER ANALYSIS; COMPUTER PROGRAM; DROSOPHILA; GENE EXPRESSION PROFILING; GENETICS; METABOLISM; METHODOLOGY; MITOCHONDRION; NUCLEAR PORE; PROTEIN ANALYSIS; PROTEIN PROTEIN INTERACTION; RIBOSOME; SACCHAROMYCES CEREVISIAE; STATISTICAL MODEL; STATISTICS;

ALGORITHMS; ANIMALS; BAYES THEOREM; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; DROSOPHILA; GENE EXPRESSION PROFILING; LIKELIHOOD FUNCTIONS; MITOCHONDRIA; NUCLEAR PORE; PROTEIN INTERACTION MAPPING; PROTEIN INTERACTION MAPS; RIBOSOMES; SACCHAROMYCES CEREVISIAE; SOFTWARE; STOCHASTIC PROCESSES;

EID: 84863525909     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/bts211     Document Type: Article

References (43)

1. Airoldi, E.M. et al. (2008) Mixed membership stochastic blockmodels. J. Machine Learn. Res., 9, 1981-2014.
2. Arbeitman, M.N. et al. (2002) Gene expression during the life cycle of Drosophila melanogaster. Science, 297, 2270-2275.
3. Ball, B. et al. (2011) Efficient and principled method for detecting communities in networks. Physical Rev. E, 84, 036103.
4. Bandyopadhyay, S. et al. (2010) Rewiring of genetic networks in response to DNA damage. Science, 330, 1385-1389.
5. Bayati, M. et al. (2006) A simpler max-product maximum weight matching algorithm and the auction algorithm. IEEE Trans. Inf. Theory, 2006, 557-561.
6. Bayati, M. et al. (2008) Max-product for maximum weight matching: convergence, correctness, and LP duality. IEEE Trans. Inf. Theory, 54, 1241-1251.
7. Baym, M. et al. (2008) High-resolution modeling of cellular signaling networks. In Proceedings of the 12th Annual International Conference on Research in Computational Molecular Biology RECOMB'08. Singapore, Springer, Berlin, Heidelberg, pp. 257-271.
8. Bickel, P.J. and Chen, A. (2009)Anonparametric view of network models and Newman- Girvan and other modularities. Proc. Natl. Acad. Sci., 106, 21068-21073.
9. Blei, D.M. et al. (2003) Latent dirichlet allocation. J. Mach. Learn. Res. (JMLR), 3, 993-1022.
10. Clauset, A. et al. (2004) Finding community structure in very large networks. Phys. Rev. E Stat. Nonlin. Soft Matter Phy., 70 (6 Pt 2), 66111.
11. Fu, W. et al. (2009) Dynamic mixed membership blockmodel for evolving networks. In ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning ACM.
12. Grünwald, D. et al. (2011) Nuclear export dynamics of RNA-protein complexes. Nature, 475, 333-341.
13. Hanneke, S. et al. (2010) Discrete temporal models of social networks. Electronic J. Stat., 4, 585-605.
14. Haqqani, A.S. et al. (2008) Quantitative protein profiling by mass spectrometry using label-free proteomics. Methods Mol. Biol., 439, 241-256.
15. Henderson, K. et al. (2010) HCDF: a hybrid community discovery framework. SDM, 2010, 754-765.
16. Hofman, J.M. and Wiggins, C.H. (2008) Bayesian approach to network modularity. Physical Rev. Lett., 100, 258-701.
17. Jansen, R. et al. (2002) Relating whole-genome expression data with protein-protein interactions. Genome Res., 12, 37-46.
18. Karrer, B. et al. (2008) Robustness of community structure in networks. Phys. Rev. E Stat. Nonlin. Soft Matter Phys., 77 (4 Pt 2), 046119.
19. Kass, R.E. and Raftery, A.E. (1995) Bayes factors. J. Am. Stat. Assoc., 90, 773-795.
20. Koller, D. and Friedman, N. (2009) Probabilistic Graphical Models: Principles and Techniques. Cambridge, MA, MIT Press.
21. Leskovec, J. et al. (2005) Graphs over time. In Proceeding of the EleventhACMSIGKDD International Conference on Knowledge Discovery in Data Mining - KDD '05, p. 177.
22. Liu, Q. et al. (2006) Reconstitution, activities, and structure of the eukaryotic RNA exosome. Cell, 127, 1223-1237.
23. Metodiev, M.D. et al. (2009) Methylation of 12S rRNA is necessary for in vivo stability of the small subunit of the mammalian mitochondrial ribosome. Cell Metabol., 9, 386-397.
24. Mitchell, P. et al. (1997) The exosome: a conserved eukaryotic RNAprocessing complex containing multiple 3' → 5' exoribonucleases. Cell, 91, 457-466.
25. Navlakha, S. and Kingsford, C. (2011) Network archaeology: uncovering ancient networks from present-day interactions. PLoS Comput. Biol., 7, e1001119.
26. Palla, G. et al. (2005) Uncovering the overlapping community structure of complex networks in nature and society. Nature, 435, 814-818.
27. Park, Y. and Bader, J.S. (2011) Resolving the structure of interactomes with hierarchical agglomerative clustering. BMC Bioinform., 12 (Suppl. 1), S44.
28. Park, Y. et al. (2010) Dynamic networks from hierarchical bayesian graph clustering. PloS one, 5, e8118.
29. Pemberton, L.F. et al. (1998) Transport routes through the nuclear pore complex. Curr. Opin. Cell Biol., 10, 392-399.
30. Petrossian, T.C. and Clarke, S.G. (2009) Multiple motif scanning to identify methyltransferases from the yeast proteome. Mol. Cell. Proteomics, 8, 1516-1526.
31. Pu, S. et al. (2009) Up-to-date catalogues of yeast protein complexes. Nucleic Acids Res., 37, 825-831.
32. Sardiu, M.E. and Washburn, M.P. (2011) Construction of protein interaction networks based on the label-free quantitative proteomics. Method. Mol. Biol., 781, 71-85.
33. Saveanu, C. (2001) Identification of 12 new yeast mitochondrial ribosomal proteins including 6 that have no prokaryotic homologues. J. Biol. Chem., 276, 15861-15867.
34. Schlenstedt, G. et al. (1997) Yrb4p, a yeast ran-GTP-binding protein involved in import of ribosomal protein L25 into the nucleus. EMBO J., 16, 6237-6249.
35. Schwarz, G. (1978) Estimating the dimension of a model. Ann. Stat., 6, 461-464.
36. Song, L. et al. (2009) KELLER: estimating time-varying interactions between genes. Bioinformatics, 25, i128-i136.
37. Stark, C. et al. (2006) BioGRID: a general repository for interaction datasets. Nucleic Acids Res., 34, D535.
38. Strambio-De-Castillia, C. et al. (2010) The nuclear pore complex: bridging nuclear transport and gene regulation. Nature Rev. Mol. Cell. Biol., 11, 490-501.
39. Tu, B.P. et al. (2005) Logic of the yeast metabolic cycle: temporal compartmentalization of cellular processes. Science, 310, 1152-1158.
40. Wu, Z. et al. (2004) A model-based background adjustment for oligonucleotide expression arrays. J. Am. Stat. Assoc., 99, 909-917.
41. Yedidia, J. et al. (2005) Constructing free-energy approximations and generalized belief propagation algorithms. IEEE Trans. Inf. Theory, 51, 2282-2312.
42. Yoo, C.J. and Wolin, S.L. (1994) La proteins from Drosophila melanogaster and Saccharomyces cerevisiae: a yeast homolog of the La autoantigen is dispensable for growth. Mol. Cell. Biol., 14, 5412-5424.
43. Zhu, W. et al. (2010) Mass spectrometry-based label-free quantitative proteomics. J. Biomed. Biotechnol., 2010, 840518