Gene Prediction Algorithm Based On Phellinus Igniarius Full Sequence

With the development of modern gene sequencing technology,more and more gene data appear in front of researchers.These generous growth sequences do not equal information knowledge.How to get useful knowledge from a great deal of genetic data by means of various existing technologies is the main problem at present.Therefore,the development of data analysis algorithms and tools has been drawn more and more attention.Phellinus igniarius,as a kind of fungus with high medicinal value,is still in its infancy due to technology blockade in foreign countries.Therefore,the research on the genetic level has important meaning for the molecular mechanism of Phellinus igniarius and the optimization of the experimental environment,and finding effective method for Phellinus igniarius gene prediction is the main content of this article.In this paper,bioinformatics methods were used to analyze and process the gene expression data to discover potential Phellinus igniarius gene expression regions.In this study,three cycles of exon of genes were selected as the starting point,combined with power spectrum analysis method,based on classical Fourier transform,the knowledge mining in bioinformatics was converted into signal processing with computer as auxiliary means.On the one hand,the three-periodic analysis of the known Phellinus igniarius and its related species in the NCBI database was used to determine the threshold value of the gene recognition and to divide the selected segments according to the data characteristics.On the other hand,The self-adaptive sliding frame should be used to solve the prediction instability and boundary ambiguity caused by the fixed sliding frame,and to establish an adaptive three-periodic gene prediction model.Sequence alignment is a fundamental problem in bioinformatics.Since the structure and function of white matter are more conservative than those of a sequence,roughly speaking,if the similarity between sequences exceeds 30%,they are likely to be homologous In this paper,we propose a fuzzy matching algorithm that incorporates proper residue merging with the actual problems.While maintaining the main information of the original protein sequence,it reduces the complexity of the protein system,reduces the number of types of words in the non-aligned sequence analysis,and resolves the word frequency Vector dimension is too large,so as to improve the efficiency of sequence analysis.In this paper,pretreatment of Phellinus linteus whole sequence and protein data,gene-matching algorithm and three-period predictive analysis algorithm are designed to predict potential Phellinus linteus locus and provide an effective decision-making basis for biological experimenters And algorithm support.Part of the Phellinus igniarius gene prediction results have been validated in the NCBI public database,and the prediction accuracy and model stability are better.