Application Of Bioinformatics On Common Corn Disease

With the implementation of human genome project, various organisms of gene sequences have been sequenced, large number of genetic data grow explosively, It is crucial to search ways to select useful information from the massive data, and mine functions of new gene sequence as well as discover the unknown gene from gene family, these all contributes to research on evolution and development of living creatures. Facing with the large number of genetic data, traditional manual sequence alignment is no longer suitable, instead of using computer hardware and mathematical algorithms, and other scientific means of it is automatic comparison. Biological gene sequence was used as an important means in the research of molecular biology, mainly for pairwise alignment and multiple sequence alignment, pairwise alignment mainly for two sequence alignment, by double sequence we can accurately find the two gene sequences between the similarities and differences, and multiple sequence alignment can determine the relationship between a group of gene sequence, when the two sequence alignment is not a good description of the sequence relationship, through the introduction of a group of gene sequence alignment, in the environment of multiple sequence alignment, some genes of the conservative section and special structure and functions can be identified.Many of the known biological information software for sequence alignment use computer science technology of computer science, the algorithm also varied, but each algorithm has its advantages and disadvantages, accuracy and speed is difficult to take into account. So a continuous research method, sequence alignment algorithm, has become a hot topic. The multiple sequence alignment algorithm is studied in detail, the current study uses Clustal W algorithm, progressive alignment algorithm is widely used in the T-COFFEE algorithm, PRRP algorithm, iterative algorithm, DiAlign algorithm and Muscle algorithm, learning the main idea of two kinds of algorithm, the algorithm principle and the advantages and disadvantages, through the study of these excellent algorithms, based on graph theory, combine POA algorithm and hidden Markov model, we get PHMM algorithm, the new algorithm avoids the first step random sequence progressive alignment algorithm, but the sequence from POA map select join nodes contained most of the branches, the distance matrix calculation of this sequence with other sequences, and then we construct a guide tree, and build guide tree with progressive alignment according to the hidden Markov model, in order to get more accurate The comparison can be made using the iterative method. This choice based on graph theory in a large amount of sequence group has obvious advantages, choosing optimal sequence can greatly reduce the possibility, in subsequent iterations of the algorithm, but also it can effectively iterative progressive alignment, reduce the number of iterations. And subsequent use of the hidden Markov model can avoid the effect of the penalty points on the scoring results. This algorithm breaks the traditional linear sequence alignment, and combines the graph algorithm with the mathematical model for the first time, which has important significance for the follow-up study.Finally, we make verification according to the algorithm of data based on the data of grain corn which is important for human life, corn is one of the three major grain products, but due to various diseases, the annual yield of maize yield is much lower than expected, resulting in a waste of food, in order to reduce the waste and increase the yield of maize, this paper studys the corn common disease, the same residues using the maize PHMM algorithm to find conserved regions of common diseases in the found similarities, and hope to find the cure and prevent or reduce the probability of occurrence of maize disease from gene, thus to enhance the yield of Maize by using the method of non environmental pollution.