ANALYSIS OF DNA FINGERPRINT DATA BY CLUSTERING-BASED ALGORITHMS

Year 2017, Volume: Volume 2 Issue: İssue 1 (1) - 2.İnternational Congress Of Forensic Toxicology, 120 - 120, 16.02.2017

Mehmet Kadir Erdoğan

Abstract

DNA
fingerprinting is a technique which allows the analysis of genomic relatedness
between DNA patterns. Various DNA fingerprinting techniques have multiple
applications in the area of molecular diagnostics, medical diagnosis, forensic
science, epidemiological analyses, parentage testing, food industry,
agriculture, environmental microbiology, ecology, and many others. After
fingerprinting of DNA by several techniques such as RFLP, ARDRA, rep-PCR, RISA,
DGGE, there is a major difficulty for aligment of multiple peak sets of DNA
fingerprinting image. Although bioinformatics software applications are
commercially available for gel analyses (e.g., BioNumerics and GelCompar,
Applied Math. Sint-Martens-Latem, Belgium), they are usually expensive and the
types of analysis included are limited. In order to analyse the DNA fingerprint
data, several clustering-based algorithmic techniques are widely used such as
self-organizing maps, hierarchical clustering, graph-theoretical approaches and
model-based clustering. These are free and flexible programs, therefore
desirable techniques for the analysis of DNA fingerprinting data.

The choice of
the clustering algorithm is generally dependent on both evaluation criteria and
the user’s experience. Data distrubition and requirements of application are
the main performance tools for different clustering algorithms.

Keywords

ANALYSIS OF DNA FINGERPRINT DATA BY CLUSTERING-BASED ALGORITHMS

References

• Mehmet Kadir ERDOĞAN Department of Biology, Faculty of Arts and Sciences, Bingöl University, 12000, Bingöl, Turkey