Research On RBP Binding Site Prediction Model Based On Deep Learning

In bioinformatics,binding site analysis of RNA-binding protein(RBP)has been a time-consuming and labor-intensive study.With the development of big data and artificial intelligence and the perfection of biological genome sequencing data,the data generated during gene expression analysis are analyzed and analyzed by computer to find out the biological laws,which greatly reduces the difficulty of the binding of RNAbinding proteins.At the current rapid development of artificial intelligence,many researchers have invested in the application and improvement of machine learning algorithms.Research on the binding sites of RNA-binding proteins based on machine learning has become a popular research in bioinformatics in recent years.One of the topics.Different from previous methods and experimental processes for biological information,this paper mainly studies and analyzes the binding site sequence data of RNA binding protein through shallow machine learning algorithm and deep learning algorithm,and analyzes sequence and structural properties of RBP binding site and prediction the binding site sequence of the RNA binding protein.The main research contents mainly include the following two aspects:1.Construct a deep convolutional network CNN network model CRSDeep,analyze the RNA binding protein(RBP)data by model,analyze the specific binding gene sequence sites and structural motifs of RNA binding proteins,and analyze the experimental results accordingly.2.The network combining deep convolutional neural network CNN and circulating neural network RNN is applied to the gene sequence data of RNA-binding protein.The genomic sequence prediction model GDeepsp is used to analyze and predict the gene sequence of RNA-binding protein,and the original data is used.Corresponding comparison.In this paper,we use the RBP-related dataset in biological information to verify the correctness and efficiency of the prediction model based on deep learning RBP binding sites.The sequence datasets in the CLIP-seq dataset are used to conduct experiments and verify the accuracy of the algorithm model.The research results of this paper have greatly shortened the experimental cost and experimental cycle of bioinformatics-related experimental analysis,and provide corresponding support for bioinformatics researchers to find the experimental data needed from the data of RNAbinding proteins.