Abstract
The term Epigenetics science is an element of a ‘postgenomic’ analysis paradigm that has more and more place in the theoretical model of a unidirectional causative link from DNA → polymer → supermolecule → constitution. Epigenetics virtually means that “above” or “on high of” biological science. It refers to explicitly modifications to deoxyribonucleic acid that flip genes “on” or “off.” These changes don’t amendment the deoxyribonucleic acid sequence, however instead, they have an effect on however cells “read” genes. Epigenetic changes alter the natural object of DNA. One example of associate degree epigenetic amendment is DNA methylation—the addition of a alkyl group, or a “chemical cap,” to a part of the DNA molecule, that prevents sure genes from being expressed. In this paper, an algorithm i-DNA-M has been proposed which would improve the result of the mining intelligent patters in dataset. Patterns further helps to reconstruct phylogenetic network. The idea behind i-DNA-M is rearranging the input sequences in a way that the new arrangement gives a better tree, since the patterns or motifs affects the outcomes of phylogenetic network.
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Acknowledgments
The authors thank Dr. Ashok K. Chauhan, Founder President, Amity University, for his support and motivation along with providing us with the necessary infrastructure for research.
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Appendix
Appendix
Appendix, shows graphical representation of phylogenetic network after rearranging sequences through i-DNA-M algorithm. See Figures 1, 2, 3, 4, 5, 6, 7 and 8.
Phylogenetic network construction by neighbor joining algorithm after i-DNA-M algorithm
Result after bootstrap test of phylogenetic network construction by neighbor joining algorithm after i-DNA-M algorithm
Phylogenetic network construction by minimum evolution algorithm after i-DNA-M algorithm
Result after bootstrap test of phylogenetic network construction by minimum evolution algorithm after i-DNA-M algorithm
Phylogenetic network construction by maximum parsimony algorithm after i-DNA-M algorithm
Result after bootstrap test of phylogenetic network construction by maximum parsimony algorithm after i-DNA-M algorithm
Phylogenetic network construction by UPGMA algorithm after i-DNA-M algorithm
Result after bootstrap test of phylogenetic network construction by UPGMA algorithm after i-DNA-M algorithm
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Shamita, M., Richa, S. (2016). Epigenetic and Hybrid Intelligence in Mining Patterns. In: Satapathy, S., Mandal, J., Udgata, S., Bhateja, V. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 435. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2757-1_39
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DOI: https://doi.org/10.1007/978-81-322-2757-1_39
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