De Novo Prediction Of Drosophila’s Cis-regulatory Modules Through Integrative Analysis Of ChIP Datasets

Since the cost of sequencing genes in bioinformatics has fallen drastically,especially the widespread use of the ChIP-chip and ChIP-seq transcription sequencing technologies what can identify the DNA sequence of a large number of factors in a very short time.Generating a huge set of ChIP gene data,which not only provided experimental evidence for the further development of the research,but also brought great challenges.Although in recent years,the emergence of third-generation sequencing technology has enabled the detection of 10 bases per second and the read length can reach 10Kb-15Kb,its development is not mature enough,and the data in existing databases is still a little.Therefore,this paper uses the ChIP dataset as research content.The model organism Drosophila has completed the sequencing of the genome in 2003,and as the research progresses,the understanding of the Drosophila gene has become more and more in depth.It has fast breeding,genetic variation,and characterize the variation of the obvious characteristics.Therefore,this paper uses the data of Drosophila as the research object.Abnormal expression of genes may lead to the production of many diseases,and abnormal production of cis-regulatory modules is the main cause of abnormal gene expression.By integrating many ChIP datasets to identify the cis-regulatory modules in the genome、the regulatory network for gene construction、understanding the molecular mechanisms of gene transcriptional regulation and even the understanding of disease mechanisms have important implications.But so far,we know very little about the cis-regulatory module of eukaryotes,then in the field of bioinformatics in the whole genome,using the method of re-predicting eukaryotes to predict the cis-regulatory module is even fewer.Now,bioinformatics scholars and experts have designed many tools for recognizing cis-regulatory modules.The most common method is computer statistics.The latest method for predicting cis-regulatory modules from scratch is DePCRM,but the algorithm is too complicated.And many of the predicted cis-regulatory modules are hypothetical and have no accuracy.Therefore,this paper proposes a new research idea that integrates different tissues,cell types,physiological stages,and different experimental conditions.The Drosophila model organism ChIP dataset studies its symbiosis model,which can realize the whole genome prediction of cis-regulatory modules in the whole genome,using the motif discovery algorithm FisherMP,the motif similarity measure SPIC,and the motif The clustering algorithm CLIMP predicts the drosophila cis-regulatory module from scratch by integrating various specific information of the cis-regulatory module.This algorithm is compared with the existing DePCRM algorithm in the de novo prediction of drosophila cis-regulatory module.This algorithm is superior to DePCRM in speed and accuracy.