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Synopsis
Biomedical systems are characterized by their emergent behavior, with overall dynamics of the system arising from the multiplicity of their interactions. Even though these interactions can be directly investigated, it is often difficult to link them directly to the phenomena observed at the system level.
Epigenetic regulation provides a typical example of emergent system behavior. A large number of mechanisms are involved, e.g., DNA methylation and histone modification among others, and all contribute to controlling whether genes are expressed. Research has resulted to date in a better description of each mechanism, but a quantitative description of the interactions and their contribution to overall system evolution remains a challenge.
In this context, in vitro and in vivo studies need to be complemented by a third branch of research, namely, in silico investigation, which can contribute in several ways. It enables a better analysis of the...
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References
Barat A, Ruskin HJ (2010) A manually curated novel knowledge management system for genetic and epigenetic molecular determinants of colon cancer. Open Colorectal Cancer J 3:36–46
Bock C, Lengauer T (2008) Computational epigenetics. Bioinformatics 24(1):1–10
Clark C, Palta P, Joyce CJ, Scott C, Grundberg E, Deloukas P, Palotie A, Coffe AJ (2012) A comparison of the whole genome approach of MeDIP-Seq to the targeted approach of the infinium HumanMethylation450 BeadChip® for methylome profiling. PLoS One 7(11):e50233
Fraga MF, Agrelo R, Esteller M (2007) Cross-talk between aging and cancer. Ann N Y Acad Sci 1100(1):60–74
Knudson A (2001) Two genetic hits (more or less) to cancer. Nat Rev Cancer 1(2):157–162
Lan X, Adams C, Landers M, Dudas M, Krissinger D, Marnellos G, Bonneville R, Xu M, Wang J, Huang TH-M, Meredith G, Jin VX (2011) High resolution detection and analysis of CpG dinucleotides methylation using MBD-Seq technology. PLoS One 6(7):e22226
Maekita T, Nakazawa K, Mihara M, Nakajima T, Yanaoka K, Iguchi M, Arii K, Kaneda A, Tsukamoto T, Tatematsu M, Tamura G, Saito D, Sugimura T, Ichinose M, Ushijima T (2006) High levels of aberrant DNA methylation in helicobacter pylori-infected gastric mucosae and its possible association with gastric cancer risk. Clin Cancer Res 12:989–995
Morgan CC, Shakya K, Webb A, Walsh TA, Lynch M, Loscher CE, Ruskin HJ, O’Connell MJ (2012) Colon cancer associated genes exhibit signatures of positive selection at functionally significant positions. BMC Evol Biol 12:114
Perrin D, Ruskin HJ, Niwa T (2010) Cell type-dependent, infection-induced, aberrant DNA methylation in gastric cancer. J Theor Biol 264(2):570–577
Raghavan K, Ruskin HJ, Perrin D, Burns J, Goasmat F (2010) Computational micro model for epigenetic mechanisms. PLoS One 5(11):e14031
Ushijima T, Sasako M (2004) Focus on gastric cancer. Cancer Cell 5:121–125
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Ruskin, H.J., Perrin, D. (2014). Computational Methods in Epigenetic Research. In: Bell, E. (eds) Molecular Life Sciences. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6436-5_581-1
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DOI: https://doi.org/10.1007/978-1-4614-6436-5_581-1
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Publisher Name: Springer, New York, NY
Online ISBN: 978-1-4614-6436-5
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