## 3 Results  
Complexity in biological systems is predicted by describing interactions amongst different DNA structures. Graphs are emerging as indispensable tools in explaining how the DNA structure functions. We calculated topological properties that describe Lung gene networks. In Table 1, we present the SNP ID/substitution, their genomic location, and association to diseases and phenotypes. In Table 2, we show the topological and statistical properties of the non-cancer DNA network. We calculate the total adjacency index, Zagreb index 1, Platt index, density, average degree, and fractal dimension by DNA network. In Table 3, we show the topological and statistical properties of the lung cancer DNA network. We calculate equal topological and statistical properties as the non-cancer DNA network. \begin{table}
\begin{tabular}{c c c} \hline
**SNP ID/Substitution** & **Genomic Location** & **Association to Diseases and Phenotypes** \\ \hline rs10873142 [C \(>\) T] & Intron 8 & Lung cancer ([PERSON] et al., 2009) \\ \hline rs41508050 [C \(>\) T] & Exon 10 & Lung cancer ([PERSON] et al., 2009) \\ \hline rs41492849 [C \(>\) T] & Exon 12 & Lung cancer ([PERSON] et al., 2009) \\ \hline rs34005929 [G \(>\) A] & Exon 12 & Lung cancer ([PERSON] et al., 2009) \\ \hline rs1159465 [C \(>\) T] & Exon 12 & Lung cancer with ITS51 OH (P) ([PERSON] et al., 2011), (NSCLC) ([PERSON] et al., 2010) \\ \hline rs11549467 [G \(>\) A] & Exon 12 & Lung cancer ([PERSON] et al., 2009), (Associated with adenocarcinoma with p194 LOH) ([PERSON] et al., 2011b) and lung carcinoma (NSCLC) ([PERSON] et al., 2006; [PERSON] et al., 2005) \\ \hline Rs199775054 [G \(>\) C] & Exon 12 & Lung cancer ([PERSON] et al., 2009) Lung carcinoma (NSCLC) ([PERSON] et al., 2006) \\ \hline rs10645014 [C \(>\) T] & Intron 13 & Lung cancer ([PERSON] et al., 2009) \\ \hline \end{tabular}
\end{table} 
Table 1: SNP ID/substitution, genomic location, and association to diseases and phenotypes of lung cancer. Figure 6: Structure of the human HIF1A gene. In Table 4, the statistical properties of graphs \(\Gamma_{(\varphi i,\,j)}\) of sequence \((\varphi i,\,j)\) from non-cancer DNA sequences are calculated: Standard deviation; standard error; variance; mean absolute deviation; coefficient of variation; coefficient of dispersion, and Pearson's contingency coefficient. In Table 5, we show the statistical properties of lung cancer of graphs \(\Gamma_{(\varphi i,\,j)}\) of sequence \((\varphi i,\,j)\) from cancer DNA sequences. Figure 7 presents the comparison graph \(\Gamma_{(\varphi i,\,j)}\) of sequence \((\varphi i,\,j)\) from DNA sequences between non cancer and cancer rs10873142 [C \(>\) T]. The same identical results were also obtained in the comparison graph \(\Gamma(\varphi i,\,j)\) of sequence \((\varphi i,\,j)\) from DNA sequences between non cancer and cancer rs14508050 [C \(>\) T] and rs10645014 [C \(>\) T]. Figure 8 presents the comparison graph \(\Gamma_{(\varphi i,\,j)}\) of sequence \((\varphi i,\,j)\) from DNA sequences between non cancer and cancer 1 rs1492849 [C \(>\) T], cancer 2 rs34005929 [G \(>\) A], cancer 3 rs11549465 [C \(>\) T], cancer 4 rs11549467 [G \(>\) A], and cancer 5 Rs199775054 [G \(>\) C]. \begin{table}
\begin{tabular}{c c c c c} \hline
**Statistical Properties** & **Intron 8** & **Exon 10** & **Exon 12** & **Intron 13** \\ \hline Standard Deviation & 11.896 & 2.12891 & 3.464352 & 4.634643 \\ \hline Standard Error & 1.487 & 0.2703719 & 0.433044 & 0.5793303 \\ \hline Variance & 141.5149 & 4.532258 & 12.00174 & 21.47991 \\ \hline Mean Absolute Deviation & 7.617188 & 1.705515 & 2.952637 & 3.946289 \\ \hline Coefficient of Variation & 0.320701 & 0.4599039 & 0.5474532 & 0.3675553 \\ \hline Coefficient of Dispersion & 0.1318597 & 0.3387097 & 0.4869792 & 0.3016827 \\ \hline Pearson’s Contingency Coefficient & 0.9608 & 0.9487 & 0.9536 & 0.9682 \\ \hline \end{tabular}
\end{table} 
Table 4: Statistical properties of graphs \(\Gamma_{(\varphi i,\,j)}\) of sequence \((\varphi i,\,j)\) from non-cancer DNA sequences.