Research And Implementation Of A Computational Model For LncRNA Functional Similarity

In recent years,long non-coding RNA(lncRNA)have been proved to play an important role in various biological processes and are closely associated with many human diseases.However,the mechanism action of these lncRNA in diseases is not entirely clear.In addition,existing databases lack records on the function of lncRNA,and traditional biological experiments and clinical studies are costly.Therefore,it is still a challenge for bioinformatics to infer the function of lncRNA in diseases and explore their potential association.According to above background,the main work of this paper is as follows:(1)A functional similarity calculation model of IDSSIM was proposed,which aims to infer unknown functions of lncRNA after using the known functions of lncRNA and the similarities between lncRNA.The model is improved in disease similarity calculation where semantic contribution factor of information content is proposed.The semantic contribution factor quantifies the information value of different diseases through the occurrence probability of diseases in all Directed Acyclic Graphs(DAG),so as to retain the specificity of diseases and improve the accuracy of disease similarity calculation.More accurate functional similarity of lncRNA could be obtained by further processing of disease similarity.Finally,the lncRNA-disease data is applied for comparative experiments with the other three existing models in order to verify the effectiveness of the model.The Area Under the Curve(AUC)value and case study are used as evaluation strategies.The experimental results showed that the model achieved good results and made a certain contribution to the inference of the function of lncRNA.(2)Design and implement the lncRNA functional similarity calculation system.Based on the IDSSIM function similarity calculation model,this paper designed and implemented the lncRNA function similarity calculation system.The system adopts B/S structure and MTV mode logically in the software development process.The combination of HTML,CSS,Java Script and other technologies is used in the front-end page.The Django framework and the My SQL database are applied to the back-end.These technologies ensure that the system is compatible with current major browsers and can be expanded in the future according to new requirements.In addition,the system realizes the functions of query,calculation,prediction and data analysis,which provides a complete calculation process for researchers and promotes the research on the mechanism of lncRNA functional similarity.