Open Access
Issue
EPJ Nonlinear Biomed Phys
Volume 4, Number 1, December 2016
Article Number 2
Number of page(s) 15
DOI https://doi.org/10.1140/epjnbp/s40366-016-0029-5
Published online 05 May 2016
  1. Dekker J, Rippe K, Dekker M, Kleckner N. Capturing chromosome conformation. Science. 2002; 295:1306–11. [Google Scholar]
  2. Lieberman-Aiden E, van Berkum NL, Williams L, Imakaev M, Ragoczy T, Telling A, Amit I, Lajoie BR, Sabo PJ, Dorschner MO, et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science. 2009; 326(5950):289–93. [Google Scholar]
  3. Rao SS, Huntley MH, Durand NC, Stamenova EK, Bochkov ID, Robinson JT, Sanborn AL, Machol I, Omer AD, Lander ES, et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell. 2014; 159(7):1665–80. [Google Scholar]
  4. Dekker J, Misteli T. Long-range chromatin interactions. Cold Spring Harbor Perspect Biol. 2015; 7(10):019356. [Google Scholar]
  5. Ea V, Baudement MO, Lesne A, Forné T. Contribution of topological domains and loop formation to 3D chromatin organization. Genes. 2015; 6(3):734–50. [Google Scholar]
  6. Newman ME. The structure and function of complex networks. SIAM Rev. 2003; 45(2):167–256. [Google Scholar]
  7. Boccaletti S, Latora V, Moreno Y, Chavez M, Hwang DU. Complex networks: Structure and dynamics. Phys Reports. 2006; 424(4):175–308. [Google Scholar]
  8. Di Paola L, De Ruvo M, Paci P, Santoni D, Giuliani A. Protein contact networks: an emerging paradigm in chemistry. Chem Rev. 2012; 113(3):1598–613. [Google Scholar]
  9. Lesne A, Riposo J, Roger P, Cournac A, Mozziconacci J. 3D genome reconstruction from chromosomal contacts. Nat Methods. 2014; 11(11):1141–3. [Google Scholar]
  10. Cournac A, Marie-Nelly H, Marbouty M, Koszul R, Mozziconacci J. Normalization of a chromosomal contact map. BMC Genomics. 2012; 13:436. [Google Scholar]
  11. Dixon JR, Selvaraj S, Yue F, Kim A, Li Y, Shen Y, Hu M, Liu JS, Ren B. Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature. 2012; 485(7398):376–80. [Google Scholar]
  12. Babaei S, Mahfouz A, Hulsman M, Lelieveldt BP, de Ridder J, Reinders M. Hi-C chromatin interaction networks predict co-expression in the mouse cortex. PLoS Comput Biol. 2015; 11(5):1004221. [Google Scholar]
  13. Singh Sandhu K, Li G, Sung WK, Ruan Y. Chromatin interaction networks and higher order architectures of eukaryotic genomes. J Cell Biochem. 2011; 112(9):2218–21. [Google Scholar]
  14. Sandhu KS, Li G, Poh HM, Quek YLK, Sia YY, Peh SQ, Mulawadi FH, Lim J, Sikic M, Menghi F, Thalamuthu A, Sung WK, Ruan X, Fulwood MJ, Liu E, Csermely P, Ruan Y. Large-scale functional organization of long-range chromatin interaction networks. Cell Reports. 2012; 2(5):1207–19. [Google Scholar]
  15. Botta M, Haider S, Leung IX, Lio P, Mozziconacci J. Intra-and inter-chromosomal interactions correlate with CTCF binding genome wide. Mol Syst Biol. 2010; 6(1):426. [Google Scholar]
  16. Hulsman M, Dimitrakopoulos C, de Ridder J. Scale-space measures for graph topology link protein network architecture to function. Bioinformatics. 2014; 30(12):237–45. [Google Scholar]
  17. Boulos R, Arneodo A, Jensen P, Audit B. Revealing long-range interconnected hubs in human chromatin interaction data using graph theory. Phys Rev Lett. 2013; 111(11):118102. [Google Scholar]
  18. Marbouty M, Cournac A, Flot JF, Marie-Nelly H, Mozziconacci J, Koszul R. Metagenomic chromosome conformation capture (meta3c) unveils the diversity of chromosome organization in microorganisms. Elife. 2014; 3:03318. [Google Scholar]
  19. Vendruscolo M, Kussell E, Domany E. Recovery of protein structure from contact maps. Folding Design. 1997; 2(5):295–306. [Google Scholar]
  20. Serra F, Di Stefano M, Spill YG, Cuartero Y, Goodstadt M, Baù D, Marti-Renom MA. Restraint-based three-dimensional modeling of genomes and genomic domains. FEBS Lett. 2015; 589(20):2987–95. [Google Scholar]
  21. Fraser J, Rousseau M, Shenker S, Ferraiuolo MA, Hayashizaki Y, Blanchette M, Dostie J. Chromatin conformation signatures of cellular differentiation. Genome Biol. 2009; 10:37. [Google Scholar]
  22. Hirata Y, Horai S, Aihara K. Reproduction of distance matrices and original time series from recurrence plots and their applications. Eur Phys J Special Topics. 2008; 164(1):13–22. [Google Scholar]
  23. Havel TF, Kuntz I, Crippen GM. The theory and practice of distance geometry. Bull Math Biol. 1983; 45:665–720. [Google Scholar]
  24. Torgerson WS. Multidimensional scaling: I. theory and method. Psychometrika. 1952; 17(4):401–19. [Google Scholar]
  25. Zhang Z, Li G, Toh KC, Sung WK. 3D chromosome modeling with semi-definite programming and hi-c data. J Comput Biol. 2013; 20(11):831–46. [Google Scholar]
  26. Varoquaux N, Ay F, Noble W, Vert JP. A statistical approach for inferring the three-dimensional structure of the genome. Bioinformatics. 2014; 30:26–33. [Google Scholar]
  27. Wickelmaier F, Vol. 46. An introduction to MDS. Denmark: Sound Quality Research Unit, Aalborg University; 2003. [Google Scholar]
  28. Sammon JW. A nonlinear mapping for data structure analysis. IEEE Trans Comput. 1969; 18(5):401–409. [Google Scholar]
  29. Kruskal JB. Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika. 1964; 29(1):1–27. [Google Scholar]
  30. Bécavin C, Tchitchek N, Mintsa-Eya C, Lesne A, Benecke A. Improving the efficiency of multidimensional scaling in the analysis of high-dimensional data using singular value decomposition. Bioinformatics. 2011; 27(10):1413–21. [Google Scholar]

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