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End to end distance measurement algorithms in biology sequences
DNA data provide us a considerable amount of information regarding our biological data, necessary to study ourselves and learn about variant characteristics. Even being able to extract the DNA from cells and sequence it, there is a long way to process it in one step. Over past years, biologists evolved attempting to ``decipher'' the DNA code. Keyword search and string matching algorithms play a vital role in computational biology. Relationships between sequences define the biological functional and structural of the biological sequences. Finding such similarities is a challenging research area, comprehending BigData, that can bring a better understanding of the evolutionary and genetic relationships among the genes. This paper studied and analyzed different kinds of string matching algorithms used for biological sequencing, and their complexity and performance are assessed.