The Research And Implementation On Extraction And Recognition Model Of Cis Acting Elements In Eukaryotes

With the advent of the post-genome era and the deep exploration of advanced life,the research on the expression of animal and plant characters has gradually entered the gene level from the functional performance.In the process of gene expression,the presentation of gene has become another hot topic,the researchers are quite interested in this.Experts in the field of biology identify or predict new genes or species by experiment and high-throughput techniques,although the results have a certain accuracy rate but at the same time increase the burden on the experimental staff.With the help of computer science,the application of this new subject bioinformatics to solve these problems can achieve the purpose of simplifying the experimental steps and presenting the experimental results more clearly and intuitively.In the process of gene expression,transcription is the key link.In the process of transcriptional regulation,the exploration of transcription factor binding sites(ie,cis-acting elements)has become a research focus.The method of extracting and identifying cis-acting elements is also varied.In this field of research,most of the current scholars used artificial experiment and applicated foreign online platform.However,this method not only consumes resources but also unrealistic.Therefore,this paper proposes an extraction and recognition model based on cis-acting elements of eukaryotic organisms,And visualize it,and integrate the identified transcription factor binding sites to construct the database.In this paper,the Blast tool was used to compare the sequence files,and the compared results had been did the operation of internally reorganized and gap insertion to achieve multiple sequence alignment.The unsupervised graph clustering method was used to find the cluster of homologous genes,and 60 genes of five kinds of gramineous plants were divided into 10 homologous gene clusters.This study used the eukaryotes commonly used in real life as the experimental species,and used the third-order Markov model to generate the background sequence,and then used the method of searching maximal clique to identify the conspicuous motif.The accurate rate of recognition the model is 0.92,and the comprehensive evaluation value is 0.91.By combining the homologous gene alignment and the model recognition model into the system of eukaryotic cis-acting element extraction and recognition,the basic functions such as motif query,homology gene alignment and motif recognition were realized.Speaking of the running speed,there is no significant difference in the processing time between simple mode and complex crops,and the system maintained relatively good stability in the case of doubling the amount of data.