Prediction Of Associations Between LncRNA And Small Molecule Drugs Based And Its Application In Breast Cancer Data Analysis

Long non-coding RNA(lncRNA)is a type of non-coding RNA with a length greater than 200 nucleotides.Studies have found that lncRNA has complex and diverse functions,and is closely related to the occurrence and development of a variety of complex diseases.Lnc RNA is expected to be a new drug target,which has attracted the attention of academic fields and drug manufacturing fields.At present,the research on lncRNA drug targets is still in the stage of individual case analysis.Although the results of biological experiments are more reliable,they are expensive and time-consuming.This article aims to find calculation methods based on data analysis to predict the potential links between lncRNA small molecule drugs.This paper studies a framework for predicting the association between lncRNA and small molecule drugs based on functional similarity.Under this framework,the analysis of breast cancer data is carried out to realize the prediction of the association between lncRNA and small molecule drugs for breast cancer.Under this framework,the GO function enrichment analysis of lncRNA and small molecule drug target gene sets is first performed,and the similarity score between lncRNA and small molecule drugs is defined by the semantic similarity of GO annotations between gene sets.Then according to the similarity score distribution,the threshold is selected to obtain the prediction result.Further analysis summarizes the general framework for predicting the association between lncRNA and small molecule drugs,and proposes a similarity calculation method based on PPI network.By mapping lncRNA and small molecule drug target gene sets to the PPI network,and defining the similarity between lncRNA and small molecule drugs according to the shortest path between gene sets,another method for measuring the size of lncRNA and small molecule drugs is proposed.Finally,the association prediction method of lncRNA and small molecule drugs based on GO semantic similarity is applied to breast cancer related data analysis.By integrating the normal and cancer sample lncRNA and gene expression profile data in the TCGA database and the gene expression profile data before and after the action of small molecule drugs in cancer cell lines,the gene set affected by lncRNA and small molecule drugs is inferred based on differential expression analysis.Based on the semantic similarity of GO,the correlation size between lncRNA and small molecule drugs was calculated,and the prediction results of the association between lncRNA and small molecule drugs of breast cancer were obtained,and the similarity network between lncRNA and small molecule drugs was constructed,and the key lncRNA and small molecules were discovered through network analysis.node.The experimental analysis of the expression profile data of BRCA in TCGA and the expression profile data of the MCF7 cell line in LINCS,predicts the association between lncRNA and small molecule drugs in breast cancer,and the experimental results obtained the relationship between 25 lncRNA and 78 small molecule drugs 336 pairs of association relationships,and thus constructed a similarity network between lncRNA and small molecule drugs.Analyzing the key nodes in the similarity network,it is found that some of the lncRNAs such as MEG3,FGF14-AS2 and small molecule drugs such as Gefitinib and Everolimus have been confirmed to be related to breast cancer.The prediction of the association between lncRNA and small molecule drugs based on calculation method can be used as an effective auxiliary means to accelerate the development of nucleic acid drugs targeting lncRNA.This article carried out an analysis based on breast cancer data,hoping to bring useful reference to related work.