Various Defuzzification Methods on DNA Similarity Matching Using Fuzzy Inference System

M. Rahmat Widyanto; Nurtami Soedarsono; Norihiro Katayama; Mitsuyuki Nakao

doi:10.20965/jaciii.2010.p0247

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JACIII Vol.14 No.3 pp. 247-255

doi: 10.20965/jaciii.2010.p0247

(2010)

Paper:

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Various Defuzzification Methods on DNA Similarity Matching Using Fuzzy Inference System

M. Rahmat Widyanto^, Nurtami Soedarsono^,
Norihiro Katayama^, and Mitsuyuki Nakao^***

^*Faculty of Computer Science, University of Indonesia, Depok Campus, Depok 16424, West Java, Indonesia

^**Faculty of Dentistry, University of Indonesia Salemba Campus, Jakarta, Indonesia

^***Biomodeling Laboratory, Department of Applied Information Sciences, Graduate School of Information Sciences, Tohoku University, 6-3-09 Aoba, Aramaki-aza, Aoba-ku, Sendai 980-8579, Japan

Received:

December 8, 2009

Accepted:

February 9, 2010

Published:

April 20, 2010

Keywords:

DNA similarity matching, fuzzy inference system, defuzzification method, short tandem repeat

Abstract

A DNA similarity matching using fuzzy inference system is proposed to measure a similarity between human STR (Short Tandem Repeat) based DNA (Deoxyribonucleic Acid) profiles. Moreover, various defuzzification methods are also tested to observe their behavior on different DNA data characteristics. Experiment on real human STR based DNA profile data shows that the proposed DNA similarity matching produces more realistic similarity values compared to those of the conventional one. Experiment on various defuzzification methods on DNA similarity matching shows that Sugeno defuzzification method is more suitable than those of other defuzzification methods.

Cite this article as:

M. Widyanto, N. Soedarsono, N. Katayama, and M. Nakao, “Various Defuzzification Methods on DNA Similarity Matching Using Fuzzy Inference System,” J. Adv. Comput. Intell. Intell. Inform., Vol.14 No.3, pp. 247-255, 2010.

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References

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This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] S. Axelrad, “Use of Forensic DNA Database Information for Medical or Genetic Research,” 2006.

[2] [2] Interpol, “Disaster Victim Identification,” ICRC, 2002.

[3] [3] H. Kitakami, T. Shin-I, K. Ikeo, Y. Ugawa, N. Saitou, T. Gojobori, Y. Tateno, et al., “DNA Database Management System,” Proc. of 28th Annual Hawaii Int. Conf. on System Sciences, 2005.

[4] [4] J. Butler et al., “STR Analysis,” Advancing Criminal Justice Through DNA Technology,
http://www.dna.gov/basics/analysis/straccessed on June 26, 2009.

[5] [5] R. C. Michaelis et al., “A Litigator’s Guide to DNA From the Laboratory to the Courtroom,” Elsevier, 2008.

[6] [6] F. X. Ricaut, C. Keyser-Tracqui, E. Crube’zy, and B. Ludes, “STR-genotyping from Human Medieval Tooth and Bone Samples,” Forensic Science International, Vol.151, pp. 31-35, 2005.

[7] [7] A. M. Roccazzello, G. Tringali, A. Barbaro, P. Cormaci, and E. Insirello, “Simultaneous Estimation of a Y-specific fragment, an X-specific Fragment and Sex Determination of Forensic Studies in Real-time PCR,” Forensic Science International, Vol.146(S), pp. 165-166, 2004.

[8] [8] C. M. Ruitberg, D. J. Reeder, and J. M. Butler, “STRBase: a Short Tandem Repeat DNA Database Human Identity Testing Database,” Nucleic Acid Research, Vol.29, No.1, 2001.

[9] [9] J. Butler and D. Reeder, “Short Tandem Repeat DNA,”
http://www.cstl.nist.gov/div831/strbase
accessed on June 26, 2009.

[10] [10] J. Butler, “NIST – Developed Software,” STRBase,
http://www.cstl.nist.gov/biotech/strbase/software.htm
accessed on June 26, 2009.

[11] [11] K. H. Lee, “First Course on Fuzzy Theory And Application,” Springer, 2004.

[12] [12] J. Butler et al., “Steps in DNA Sample Processing,” Advancing Criminal Justice Through DNA Technology,
http://www.dna.gov/basics/analysis/steps/
accessed on June 26, 2009.

[13] [13] A. A. Westen, R. R. R. Gerretsen, and J. R. G. Maat, “Femur, Rib, and Tooth Sample Collection for DNA Analysis in Disaster Victim Identification (DVI),” Forensics Science Medical Pathology, Vol.22, 2007.

[14] [14] A. Konar, “Computational Intelligence,” Springer, 2005.

[15] [15] L. A. Zadeh, “Fuzzy Sets,” Information and Control, Vol.12, pp. 338-353, 1965.

[16] [16] G. Taoufik and D. Benslimean, “Fuzzy Similarity Measure,” Springer, 2006.

Various Defuzzification Methods on DNA Similarity Matching Using Fuzzy Inference System

M. Rahmat Widyanto*, Nurtami Soedarsono**, Norihiro Katayama***, and Mitsuyuki Nakao***

M. Rahmat Widyanto^, Nurtami Soedarsono^,
Norihiro Katayama^, and Mitsuyuki Nakao^***