A novel human STR similarity method using cascade statistical fuzzy rules with tribal information inference

Muhammad Rahmat Widyanto, Reggio N. Hartono, Nurtami Soedarsono

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

A novel human STR (Short Tandem Repeat) similarity method using cascade statistical fuzzy rules with tribal information inference is proposed. The proposed method consists of two cascade Fuzzy Inference Systems (FIS). The first FIS is to discriminate the tribal similarity, and the second FIS is to calculate the STR similarity. By using the allele marker's statistical distribution probability density function as the membership function in the Fuzzy Rules of the first FIS, the new method makes it possible to tell the tribal similarity between two STR profiles. A 727 data acquired from tribal groups of Indonesia is used to examine the method produced promising result, being able to indicate higher tribal similarity score within a tribal group and lower similarity between tribal groups. In the light of Indonesia's diverse tribal groups, these properties are able to be leveraged as a new way to improve the versatility of existing DNA matching algorithm.

Original languageEnglish
Pages (from-to)3103-3111
Number of pages9
JournalInternational Journal of Electrical and Computer Engineering
Volume6
Issue number6
DOIs
Publication statusPublished - 1 Jan 2016

Keywords

  • Cascade fuzzy rules
  • Short tandem repeat
  • Statistical distribution
  • Tribal information

Fingerprint

Dive into the research topics of 'A novel human STR similarity method using cascade statistical fuzzy rules with tribal information inference'. Together they form a unique fingerprint.

Cite this