Abstract
The computer technology has advanced profoundly that the application seems to have no limit. Equipped with programming, our research team has created programs that could be used practically in the field of chemistry. The purpose of this paper is not on the making useful tools for science, but on using analytic tools based on computer programming to find additional evidence that supports a theory. The Suport Vector Machine (also known as its acronym, SVM) is used frequently in genetic analysis to find certain patterns in DNA sequence. This paper deals with pattern similarity between rRNA of mitochondria and that of alphaproteobacteria, which is believed to be the ancestor of the mitochondria. This theory, also known as “endosymbiotic theory” has a variety of evidences and has accepted as authentic. The pattern similarity between the two organisms’ DNA sequence, which is the result of the paper would consolidate the evolutionary endosymbiosis.
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Endosymbiotic Theory. http://wikipedia.org/
Reece, J.B., et al.: Campbell Biology, Chapter 6, 9th edn, p. 109 (2013)
Mitochondria Structural Features. http://www.ccwcs.org/
Bay, K., et al.: Mitochondria share an ancestor with SAR11, a globally significant marine microbe. Science Daily, 25 July 2011. Accessed 26 July 2011
Thrash, J.C., et al.: Phylogenomic evidence for a common ancestor of mitochondria and the SAR11 clade. Scientific reports (2011)
Reddy, E.M.: Effective classification using parallel apriori: pattern analysis for effective classification using parallel apriori (2012)
Yamashita, H., Tanaka, S.: An Introduction to Support Vector Machines, pp. 6–8 (2001)
Cristianini, N., Shawe‐Taylor, J.: An Introduction to Support Vector Machines, 6th edn., pp. 34–66 (2008)
Onoda, T.: Support Vector Machine (Science of Intelligence), 2nd edn., pp. 11–108 (2008)
Agrawal, R., Srikant, R.: Fast algorithms for mining association rules in large databases. In: Proceedings of the 20th International Conference on Very Large Data Bases, Santiago, Chile, pp. 487–499, September 1994
Bayardo Jr., R.J.: Efficiently mining long patterns from databases. In: ACM SIGMOD Record, vol. 27(2). ACM (1998)
Encyclopedia Of Life. http://eol.org/pages/3349/overview
Andersson, S.G., Zomorodipour, A., Andersson, J.O., Sicheritz-Pontén, T., Alsmark, U.C., Podowski, R.M., Näslund, A.K., Eriksson, A.S., Winkler, H.H., Kurland, C.G.: The genome sequence of Rickettsia prowazekii and the origin of mitochondria. Nature 396(6707), 133–140 (1998)
The National Center for Biotechnology Information. http://www.ncbi.nlm.nih.gov/
Sykes, B.: Mitochondrial DNA and human history. The Hu man Genome. Wellcome Trust. Accessed 5 February 2012
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Lim, S.J., Bang, S.H., Kim, D.S., Yoon, T. (2014). rRNA of Alphaproteobacteria Rickettsiales and mtDNA Pattern Analyzing with Apriori & SVM. In: Peng, WC., et al. Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2014. Lecture Notes in Computer Science(), vol 8643. Springer, Cham. https://doi.org/10.1007/978-3-319-13186-3_11
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DOI: https://doi.org/10.1007/978-3-319-13186-3_11
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