Numerical analysis DNA is microscopic however; the amount of data it generates is huge. Researchers require advanced numerical techniques to manipulate and make sense of the data.
Statistics has played a part in generating "draft sequence data" mostly 10,000 base-pair fragments whose approximate chromosomal locations are known. Additional sequencing will close gaps and reduce ambiguities. Statistics is also used to design experiments to optimize information extracted from these experiments.
Computational models Researchers attempt to predict molecular behavior by describing DNA and protein molecules with equations that can be solved numerically. The massive amount of data now available allows for more accurate equations on which to base models and the ability to compare predictions with known results.
Topology or the shape and geometry of complex structures are the basic double helix structure of DNA, which provides a information about the molecule, although not complete. The details of the structure and of the different forms of DNA provide information about the biological function of DNA. In addition, the structure and formation of proteins are far more complicated than those of DNA.
Computer graphics make static and mobile images of DNA structures possible, which enables both researchers and laypersons better able to visualize and study the genome.
Microarrays are a relatively new invention that lets scientists measure something they could not measure previously. A microarray measures how much a messenger RNA of a given type is being made in a sample of tissue at a given moment, which gives a good idea of how much of the corresponding protein is being made.
Biological curiosities can be compared and contrasted in mathematics, with results that far exceed chaotic expectations and speculations. DNA is indeed fractal in certain respects of its operation as evidenced by the huge scale and scope of research completed so far. Regardless of the research, because fractals in nature are exceedingly common, their association with DNA should be anticipated. The evolution of diseases and the evolution of medicine are chronologically parallel in that the rise of the former gives rise to the latter, preferably within the same time intervals. Where medicine has failed or failed to be prompt, pandemics, epidemics, and extinction can result. Understanding and managing patterns that arise within this evolutionary dualism can lead to proactive responses to oppose pandemics, epidemics, and extinction, whereas these growth patterns and projections are also within the logic and structure of fractals, including the probability to remain constant or mutate.
