The Mathematical Expression And Application Of RNA And Protein Sequence

The essence of bioinformatics is to analyze and classify the no rules of the data to extract useful information for biological sequences comparison analysis of the development, system design, biochemical drugs, simulation, etc. The main objects of bioinformatics is nucleic acid, protein, and molecular genetic mechanism. Actually, RNA and protein is the main content of bioinformatics, because they have an important role on the growth, development and biological and genetic breeding. They not only can reappear creatures human history, but also provide scientific basis and the huge economic efficiency and the social efficiency immeasurable for medicine, agriculture and industry produce. Based on the comparative analysis of biological sequences for background. We present a new representation for RNA and protein, with the new method, we enumerate the specific application of biological sequences comparison. This research contents can be summarized as follows:1.According to the composition of RNA secondary structure, in the paper, an ond-one map is defined, which translates the nucleotide sequences into point set in 3-D space. Accroding to this mapping, the oriented cure of this sequence can be getted. Then transform the cure into characteristic vector and L/L matrix, extract the angle cosine of the characteristic vector and eigenvalue of the L/L matrix average them and use them as the feature vectors to characterize the RNA secondary structure.In the end, the similarity of the RNA secondary structures of AIMV-3 is we analyzed, making use of the matrix invariant:the average of L/L matrix eigenvalues and the distances between the characteristic vectors, which describe the invariance of the sequences.2. Apply the new representation of protein sequences. According to the composition of Protein structure, in the paper, an one-one map is defined, which translates the nucleotide sequences into point sets in 3-D space. With the help of mapping, the oriented cure of these sequences can be getted. Then transform the cure into characteristic vector and L/L matrix. Furthermore, extract the angle cosine of the characteristic vector and eigenvalue of the L/L matrix,then be averaged them and use them as the feature vectors to characterize the Protein structure. In the end, analyze the similarity of the Protein structures of eight kind of G-protein-coupled receptor making use of the matrix invariant:the average of L/L matrix eigenvalues and the distances between the characteristic vectors, which describe the invariance of the sequences or the structures have the good result.