DNA Visualization with Sacks Spiral Method: An Application in Genomic Engineering.

摘要

We introduce a new and simple technique for visualizing DNA sequences using the Sacks Spiral function, a mapping method that operates on a highly refined sequence of positive integers to highlight significant functional relationships. This tool allows the comparison of protein pairs to determine their similarities in lieu of profound biochemical analysis. As a unipolar positioning system, the Sacks Spiral reveals quadratic polynomial tendencies of certain points on a DNA or protein sequence.;Gene databanks deal with a large amount of data, where, according to NCBI, there are over 33x1010 nucleotide base pairs with an 18.2% annual increment (185th release in 8/2011). Within this deluge of data lies a wealth of valuable information related to the nature and behavior of living systems of all species. This, in return, will allow experts to enhance the knowledge base in the medical and associated sciences, ensuring the nation's ability to treat and prevent diseases.;With every new gene discovery, scientists must determine its functionality. One method for doing so is to run a similarity search algorithm associated with the databank. Different gene banks use diverse statistical approaches and algorithms to automatically find similarities between multiple sequences. However, when running distinctive algorithms for the same query, different results were attained. The discrepancy in algorithm outcomes challenged the ability to determine the exact functionality of a newly discovered protein.;Our method converses information efficiently and explicitly through a graphical means. This empowers human eyes to replace cognitive calculations with minimal perceptive inferences, and enhances the evaluation and decision making of comparing proteins, to distinguish their similarities among a group of proteins. It then allows us to easily determine the most similar protein to the newly discovered one and ultimately determine its functionality.;This work is a major step in gaining fundamental knowledge about the nature and behavior of living systems through computer engineering, computer science, bioinformatics, and deductive mathematical reasoning, thus facilitating the expansion and acceleration of genomics research and initiatives.