Table of Contents Author Guidelines Submit a Manuscript
BioMed Research International
Volume 2017 (2017), Article ID 6274513, 12 pages
https://doi.org/10.1155/2017/6274513
Research Article

A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model

School of Computer Science and Technology, Xidian University, Xi’an, Shaanxi, China

Correspondence should be addressed to Hongwei Huo; nc.ude.naidix.liam@ouhwh

Received 23 October 2016; Revised 6 March 2017; Accepted 23 March 2017; Published 11 April 2017

Academic Editor: Hesham H. Ali

Copyright © 2017 Haitao Guo and Hongwei Huo. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. Su, S. A. Teichmann, and T. A. Down, “Assessing computational methods of cis-regulatory module prediction,” PLoS Computational Biology, vol. 6, no. 12, Article ID e1001020, 2010. View at Publisher · View at Google Scholar
  2. K. Suryamohan and M. S. Halfon, “Overview article: identifying transcriptional cis-regulatory modules in animal genomes,” Wiley Interdisciplinary Reviews. Developmental Biology, vol. 4, no. 2, pp. 59–84, 2015. View at Google Scholar
  3. V. Matys, O. V. Kel-Margoulis, E. Fricke et al., “TRANSFAC® and its module TRANSCompel®: transcriptional gene regulation in eukaryotes,” Nucleic Acids Research, vol. 34, pp. D108–D110, 2006. View at Google Scholar
  4. W. B. Alkema, O. Johansson, J. Lagergren, and W. W. Wasserman, “MScan: identification of functional clusters of transcription factor binding sites,” Nucleic Acids Research, vol. 32, supplement 2, pp. W195–W198, 2004. View at Google Scholar
  5. M. Naval-Sánchez, D. Potier, G. Hulselmans, V. Christiaens, and S. Aerts, “Identification of lineage-specific cis-regulatory modules associated with variation in transcription factor binding and chromatin activity using Ornstein-Uhlenbeck models,” Molecular Biology and Evolution, vol. 32, pp. 2441–2455, 2015. View at Google Scholar
  6. C. Navarro, F. J. Lopez, C. Cano, F. Garcia-Alcalde, and A. Blanco, “CisMiner: genome-wide in-silico cis-regulatory module prediction by fuzzy itemset mining,” PLoS ONE, vol. 9, no. 9, Article ID e108065, 2014. View at Google Scholar
  7. P. Arnold, I. Erb, M. Pachkov, N. Molina, and E. van Nimwegen, “MotEvo: integrated Bayesian probabilistic methods for inferring regulatory sites and motifs on multiple alignments of DNA sequences,” BioInformatics, vol. 28, no. 4, pp. 487–494, 2012. View at Google Scholar
  8. M. Leoncini, M. Montangero, M. Pellegrini, and K. P. Tillan, “CMStalker: a combinatorial tool for composite motif discovery,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 12, no. 5, pp. 1123–1136, 2015. View at Google Scholar
  9. T. Guns, S. Hong, K. Marchal, and S. Nijssen, “Cis-regulatory module detection using constraint programming,” in Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM '10), Hong Kong, December 2010.
  10. H. Sun, T. Guns, A. C. Fierro, L. Thorrez, S. Nijssen, and K. Marchal, “Unveiling combinatorial regulation through the combination of ChIP information and in silico cis-regulatory module detection,” Nucleic Acids Research, vol. 40, no. 12, article e90, 2012. View at Publisher · View at Google Scholar
  11. L. Marsan and M.-F. Sagot, “Algorithms for extracting structured motifs using a suffix tree with an application to promoter and regulatory Site consensus identification,” Journal of Computational Biology, vol. 7, no. 3-4, pp. 345–362, 2000. View at Google Scholar
  12. S. P. Pissis, “MoTeX-II: structured MoTif eXtraction from large-scale datasets,” BMC Bioinformatics, vol. 15, no. 1, article 235, 2014. View at Google Scholar
  13. S. Levy and S. Hannenhalli, “Identification of transcription factor binding sites in the human genome sequence,” Mammalian Genome, vol. 13, no. 9, pp. 510–514, 2002. View at Publisher · View at Google Scholar
  14. S. González, B. Montserrat-Sentís, F. Sánchez et al., “ReLA, a local alignment search tool for the identification of distal and proximal gene regulatory regions and their conserved transcription factor binding sites,” Bioinformatics, vol. 28, no. 6, pp. 763–770, 2012. View at Google Scholar
  15. O. Hallikas, K. Palin, N. Sinjushina et al., “Genome-wide prediction of mammalian enhancers based on analysis of transcription-factor binding affinity,” Cell, vol. 124, no. 1, pp. 47–59, 2006. View at Publisher · View at Google Scholar
  16. H. Rouault, M. Santolini, F. Schweisguth, and V. Hakim, “Imogene: identification of motifs and cis-regulatory modules underlying gene co-regulation,” Nucleic Acids Research, vol. 42, no. 10, pp. 6128–6145, 2014. View at Google Scholar
  17. D. Potier, D. Seyres, C. Guichard et al., “Identification of cis-regulatory modules encoding temporal dynamics during development,” BMC Genomics, vol. 15, no. 1, article 534, 2014. View at Publisher · View at Google Scholar
  18. Y. Gan, J. Guan, S. Zhou, and W. Zhang, “Identifying cis-regulatory elements and modules using conditional random fields,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 11, no. 1, pp. 73–82, 2014. View at Google Scholar
  19. M. C. Frith, U. Hansen, and Z. Weng, “Detection of cis-element clusters in higher eukaryotic DNA,” BioInformatics, vol. 17, no. 10, pp. 878–889, 2001. View at Google Scholar
  20. M. C. Frith, M. C. Li, and Z. Weng, “Cluster-buster: finding dense clusters of motifs in DNA sequences,” Nucleic Acids Research, vol. 31, no. 13, pp. 3666–3668, 2003. View at Google Scholar
  21. S. Sinha, E. van Nimwegen, and E. Siggia, “A probabilistic method to detect regulatory modules,” Bioinformatics, vol. 19, no. 1, pp. i292–i301, 2003. View at Google Scholar
  22. T.-H. Lin, P. Ray, G. K. Sandve, S. Uguroglu, and E. P. Xing, “BayCis: a Bayesian hierarchical HMM for cis-regulatory module decoding in metazoan genomes,” in Proceedings of the 12th Annual International Conference on Research in Computational Molecular Biology, pp. 66–81, Springer, Singapore, 2008.
  23. A. A. Nikulova, A. V. Favorov, R. A. Sutormin, V. J. Makeev, and A. A. Mironov, “CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation,” Nucleic Acids Research, vol. 40, no. 12, p. e93, 2012. View at Google Scholar
  24. S. Weingarten-Gabbay and E. Segal, “The grammar of transcriptional regulation,” Human Genetics, vol. 133, no. 6, pp. 701–711, 2014. View at Google Scholar
  25. G. Stormo, “DNA binding sites: representation and discovery,” Bioinformatics, vol. 16, no. 1, pp. 16–23, 2000. View at Google Scholar
  26. V. Matys, O. Kel-Margoulis, E. Fricke et al., “TRANSFAC® and its module TRANSCompel®: transcriptional gene regulation in eukaryotes,” Nucleic Acids Research, vol. 34, supplement 1, pp. D108–D110, 2006. View at Publisher · View at Google Scholar
  27. E. Portales-Casamar, S. Thongjuea, A. Kwon et al., “JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles,” Nucleic Acids Research, vol. 38, pp. D105–D110, 2009. View at Google Scholar
  28. F. Garcia, F. J. Lopez, C. Cano, and A. Blanco, “FISim: a new similarity measure between transcription factor binding sites based on the fuzzy integral,” BMC Bioinformatics, vol. 10, no. 1, article 224, 2009. View at Google Scholar
  29. E. Georgii, S. Dietmann, T. Uno, P. Pagel, and K. Tsuda, “Enumeration of condition-dependent dense modules in protein interaction networks,” Bioinformatics, vol. 25, pp. 933–940, 2009. View at Google Scholar
  30. S. Yu, “Hidden semi-Markov models,” Artificial Intelligence, vol. 174, no. 2, pp. 215–243, 2010. View at Google Scholar
  31. R. Durbin, S. R. Eddy, A. Krogh, and G. Mitchison, Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids, Cambridge University Press, Cambridge, UK, 1998.
  32. D. Xie, J. Cai, N.-Y. Chia, H. H. Ng, and S. Zhong, “Cross-species de novo identification of cis-regulatory modules with GibbsModule: application to gene regulation in embryonic stem cells,” Genome Research, vol. 18, no. 8, pp. 1325–1335, 2008. View at Google Scholar
  33. K. Klepper, G. K. Sandve, O. Abul, J. Johansen, and F. Drablos, “Assessment of composite motif discovery methods,” BMC Bioinformatics, vol. 9, article 123, 2008. View at Google Scholar
  34. A. Ivan, M. S. Halfon, and S. Sinha, “Computational discovery of cis-regulatory modules in Drosophila without prior knowledge of motifs,” Genome Biology, vol. 9, no. 1, p. R22, 2008. View at Google Scholar
  35. M. Burset and R. Guigó, “Evaluation of gene structure prediction programs,” Genomics, vol. 34, no. 3, pp. 353–367, 1996. View at Google Scholar
  36. W. W. Wasserman and J. W. Fickett, “Identification of regulatory regions which confer muscle-specific gene expression,” Journal of Molecular Biology, vol. 278, no. 1, pp. 167–181, 1998. View at Publisher · View at Google Scholar
  37. S. M. Gallo, D. T. Gerrard, D. Miner et al., “REDfly v3.0: toward a comprehensive database of transcriptional regulatory elements in Drosophila,” Nucleic Acids Research, vol. 39, pp. D118–D123, 2011. View at Google Scholar