Diagnosis of Lung Cancer by Fractal Analysis of Damaged DNA
Cancer starts when cells in a part of the body start to grow out of control. In fact cells become cancer cells because of DNA 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 study the cancer g...
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description | Cancer starts when cells in a part of the body start to grow out of control. In fact cells become cancer cells because of DNA 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 study the cancer genes, DNA walk plots of genomes of patients with lung cancer were generated using a program written in MATLAB language. The data so obtained was checked for fractal property by computing the fractal dimension using a program written in MATLAB. Also, the correlation of damaged DNA was studied using the Hurst exponent measure. We have found that the damaged DNA sequences are exhibiting higher degree of fractality and less correlation compared with normal DNA sequences. So we confirmed this method can be used for early detection of lung cancer. The method introduced in this research not only is useful for diagnosis of lung cancer but also can be applied for detection and growth analysis of different types of cancers. |
doi_str_mv | 10.1155/2015/242695 |
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In fact cells become cancer cells because of DNA 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 study the cancer genes, DNA walk plots of genomes of patients with lung cancer were generated using a program written in MATLAB language. The data so obtained was checked for fractal property by computing the fractal dimension using a program written in MATLAB. Also, the correlation of damaged DNA was studied using the Hurst exponent measure. We have found that the damaged DNA sequences are exhibiting higher degree of fractality and less correlation compared with normal DNA sequences. So we confirmed this method can be used for early detection of lung cancer. The method introduced in this research not only is useful for diagnosis of lung cancer but also can be applied for detection and growth analysis of different types of cancers.</description><identifier>ISSN: 1748-670X</identifier><identifier>EISSN: 1748-6718</identifier><identifier>DOI: 10.1155/2015/242695</identifier><identifier>PMID: 26539245</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Algorithms ; Computational Biology ; Diagnosis, Computer-Assisted ; DNA Damage ; DNA, Neoplasm - blood ; DNA, Neoplasm - genetics ; Early Detection of Cancer ; Fractals ; Humans ; Lung Neoplasms - diagnosis ; Lung Neoplasms - genetics ; Sequence Analysis, DNA - statistics & numerical data ; Software</subject><ispartof>Computational and mathematical methods in medicine, 2015-01, Vol.2015 (2015), p.1-11</ispartof><rights>Copyright © 2015 Hamidreza Namazi and Mona Kiminezhadmalaie.</rights><rights>Copyright © 2015 H. Namazi and M. 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In fact cells become cancer cells because of DNA 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 study the cancer genes, DNA walk plots of genomes of patients with lung cancer were generated using a program written in MATLAB language. The data so obtained was checked for fractal property by computing the fractal dimension using a program written in MATLAB. Also, the correlation of damaged DNA was studied using the Hurst exponent measure. We have found that the damaged DNA sequences are exhibiting higher degree of fractality and less correlation compared with normal DNA sequences. So we confirmed this method can be used for early detection of lung cancer. The method introduced in this research not only is useful for diagnosis of lung cancer but also can be applied for detection and growth analysis of different types of cancers.</description><subject>Algorithms</subject><subject>Computational Biology</subject><subject>Diagnosis, Computer-Assisted</subject><subject>DNA Damage</subject><subject>DNA, Neoplasm - blood</subject><subject>DNA, Neoplasm - genetics</subject><subject>Early Detection of Cancer</subject><subject>Fractals</subject><subject>Humans</subject><subject>Lung Neoplasms - diagnosis</subject><subject>Lung Neoplasms - genetics</subject><subject>Sequence Analysis, DNA - statistics & numerical data</subject><subject>Software</subject><issn>1748-670X</issn><issn>1748-6718</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>EIF</sourceid><recordid>eNqNkEFLw0AQhRdRrFZP3iVHUaI72d1sgiCU1qpQ9KLgbZlsdtNImtRsovTfm5Ja6s05zAzMx3vDI-QM6DWAEDcBha7xIIzFHjkCySM_lBDtb3f6PiDHzn1QKkAKOCSDIBQsDrg4IreTHLOycrnzKuvN2jLzxlhqU3vJypvWqBssvFGJxWqDTHCBmUm9yfPohBxYLJw53cwheZvev44f_dnLw9N4NPO1oKLxtQ0DiDloCNLuL0sTAWCNkVILi5zzMEqNkAlL0ziyDKjhzNiQI5cxwzRiQ3LX6y7bZGFSbcqmxkIt63yB9UpVmKu_lzKfq6z6UjyEOKa0E7jYCNTVZ2tcoxa506YosDRV6xRIBp3Xuobkqkd1XTlXG7u1AarWcat13KqPu6PPdz_bsr_5dsBlD8zzMsXv_H9qpkOMxR1YyIhF7AcoE5AL</recordid><startdate>20150101</startdate><enddate>20150101</enddate><creator>Namazi, Hamidreza</creator><creator>Kiminezhadmalaie, Mona</creator><general>Hindawi Publishing Corporation</general><scope>ADJCN</scope><scope>AHFXO</scope><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20150101</creationdate><title>Diagnosis of Lung Cancer by Fractal Analysis of Damaged DNA</title><author>Namazi, Hamidreza ; Kiminezhadmalaie, Mona</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c505t-cf621941c12d718f0b511fee77c5fa44468de57b3dd98f310e43ef64a4793ad83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Algorithms</topic><topic>Computational Biology</topic><topic>Diagnosis, Computer-Assisted</topic><topic>DNA Damage</topic><topic>DNA, Neoplasm - blood</topic><topic>DNA, Neoplasm - genetics</topic><topic>Early Detection of Cancer</topic><topic>Fractals</topic><topic>Humans</topic><topic>Lung Neoplasms - diagnosis</topic><topic>Lung Neoplasms - genetics</topic><topic>Sequence Analysis, DNA - statistics & numerical data</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Namazi, Hamidreza</creatorcontrib><creatorcontrib>Kiminezhadmalaie, Mona</creatorcontrib><collection>الدوريات العلمية والإحصائية - e-Marefa Academic and Statistical Periodicals</collection><collection>معرفة - المحتوى العربي الأكاديمي المتكامل - e-Marefa Academic Complete</collection><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Computational and mathematical methods in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Namazi, Hamidreza</au><au>Kiminezhadmalaie, Mona</au><au>Zaikin, Alexey</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Diagnosis of Lung Cancer by Fractal Analysis of Damaged DNA</atitle><jtitle>Computational and mathematical methods in medicine</jtitle><addtitle>Comput Math Methods Med</addtitle><date>2015-01-01</date><risdate>2015</risdate><volume>2015</volume><issue>2015</issue><spage>1</spage><epage>11</epage><pages>1-11</pages><issn>1748-670X</issn><eissn>1748-6718</eissn><abstract>Cancer starts when cells in a part of the body start to grow out of control. In fact cells become cancer cells because of DNA 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 study the cancer genes, DNA walk plots of genomes of patients with lung cancer were generated using a program written in MATLAB language. The data so obtained was checked for fractal property by computing the fractal dimension using a program written in MATLAB. Also, the correlation of damaged DNA was studied using the Hurst exponent measure. We have found that the damaged DNA sequences are exhibiting higher degree of fractality and less correlation compared with normal DNA sequences. So we confirmed this method can be used for early detection of lung cancer. The method introduced in this research not only is useful for diagnosis of lung cancer but also can be applied for detection and growth analysis of different types of cancers.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Publishing Corporation</pub><pmid>26539245</pmid><doi>10.1155/2015/242695</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Computational Biology Diagnosis, Computer-Assisted DNA Damage DNA, Neoplasm - blood DNA, Neoplasm - genetics Early Detection of Cancer Fractals Humans Lung Neoplasms - diagnosis Lung Neoplasms - genetics Sequence Analysis, DNA - statistics & numerical data Software |
title | Diagnosis of Lung Cancer by Fractal Analysis of Damaged DNA |
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