DNA Computing

Bioinformatics is an important part of nature sciences in this century. The content is enrichment at the present time. This paper includes two aspects on bioinformatics. They are DNA computing and approaching to property of DNA sequence.(1) With the rapid development of biological techniques, a new discipline named DNA computing has come into being. DNA automaton is a new content in research area of DNA computing. Inputting the same experimental DNA sequence for the DNA automaton can achieve different outputting ones to satisfy different demands. Dividing DNA sequence to CDNA and NCDNA is the popular research about DNA automaton. The theory of states transfer about DNA automaton contains two effective segmentation algorithms that are based on entropy and probability. During the process, the algorithms have been carried out by C++, and been contrasted by experimentation. The results of experiment are consistent with the classic conclusions.(2) There are many kinds of methods to investigate DNA sequence. Complex network theory is one part of it. The traditional use of complex network theory is to reveal the close relationships among the elements. The new purpose is to analyze the function of gene and specifically gene in the whole DNA sequence. It also contributes to realize the genome evolution. DNA sequence, CDNA and NCDNA can be analyzed by using complex network theory in this paper. Based on some traditional methods, the paper shows two new methods to study DNA sequence. They are prefix-suffix and probability theory. The main factors to describe complex network are clustering coefficient and degree distribution. By making use of DNA sequence and the two factors, the two methods to construct networks are feasible.