Diagnosis of skin cancer by correlation and complexity analyses of damaged DNA.

Hamidreza Namazi, Vladimir V Kulish, Fatemeh Delaviz, Ali Delaviz
Author Information
  1. Hamidreza Namazi: School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore.
  2. Vladimir V Kulish: School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore.
  3. Fatemeh Delaviz: Faculty of Chemical Engineering, Islamic Azad University (Fars Science and Research Branch), Shiraz, Iran.
  4. Ali Delaviz: Faculty of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran.

Abstract

Skin Cancer is a common, low-grade cancerous (malignant) growth of the skin. It starts from cells that begin as normal skin cells and transform into those with the potential to reproduce in an out-of-control manner. Cancer develops when DNA, the molecule found in cells that encodes genetic information, becomes damaged and the body cannot repair the damage. A DNA walk of a genome represents how the frequency of each nucleotide of a pairing nucleotide couple changes locally. In this research in order to diagnose the Skin Cancer, first DNA walk plots of genomes of patients with Skin Cancer were generated. Then, the data so obtained was checked for complexity by computing the fractal dimension. Furthermore, the Hurst exponent has been employed in order to study the correlation of damaged DNA. By analysing different samples it has been found that the damaged DNA sequences are exhibiting higher degree of complexity and less correlation compared to normal DNA sequences. This investigation confirms that this method can be used for diagnosis of Skin Cancer. The method discussed in this research is useful not only for diagnosis of Skin Cancer but can be applied for diagnosis and growth analysis of different types of cancers.

Keywords

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MeSH Term

Algorithms
DNA Damage
Fractals
Humans
Models, Theoretical
Skin Neoplasms

Word Cloud

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