Abstract: Cancer is defined as a disease that involves changes or mutations in the cell genome. Cancer genome sequencing has been recognized as a NP problem. Cancer genome sequencing includes cancer genome assembly and cancer genome alignment is through early detection improving survival opportunity of cancer patients. In this research, a bioinformatics approach uses a proposed modified Euler path on a constructed De Bruijn cancer genome graph for solving cancer genome assembly. This fast DNA algorithm fully utilizes parallelism to conquer time complexity bottleneck, and improves any cancer genome Assembly more efficient. The experimental results of cancer genome reassemble is estimated in O(n3) polynomial bound.

• Publication Date: 08-Jun-2014
• DOI: 10.15224/978-1-63248-019-4-02
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Abstract: It is a well-known fact that the DNA mutation plays a very important role in DNA sequence evolution. The backtracking problem of DNA sequence evolution in one dimensional cellular automata (CA) has ben recognized as a NP problem. In this research, a newly developed bioinformatics approach constructs a DNA sequence evolution model in using one dimensional cellular automata. Its corresponding backtracking of DNA sequence evolution is accomplished by an order-finding bioinformatics algorithm for efficient operations. The time complexity of a proposed bioinformatics approach for DNA sequence evolution in one dimensional cellular automata is found in O(n2) polynomial bound. Our newly developed algorithms for solving backtracking of DNA sequence evolution in one dimensional CA are also in O(n2) polynomial bound.

• Publication Date: 08-Jun-2014
• DOI: 10.15224/978-1-63248-019-4-03
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