Machine Learning and Artificial Intelligence for Biological Big data

  With the development of modern science and technology and gene sequencing technology, it is possible to obtain large amounts of biological data. However, human beings still can not explain the problem that scientists in the famous journal Nature put forward that human and mouse share about 99% of similar genes, but their biological characteristics are very different. The research direction of this paper is to solve the data mining theory, technology and method of big biological data through machine learning and artificial intelligence.

  The main research directions are as follows: RNA Structure Analysis and PredictionAnalysis and prediction of siRNAAnalysis of MicroRNAs and Prediction of Target GenesLncRNA and Tumors.

1. RNA Structure Analysis and Prediction

  RNA and DNA play an equally important role in the course of biological evolution. Understanding the structure of RNA can speculate its function and design new drugs for the treatment of cancer and other difficult diseases. It is a frontier academic problem in the world. This RNA structure prediction direction, through bioinformatics methods to predict RNA structure, and with the PLA Academy of Sciences, the Fourth Military Medical University, the United States of America, famous scientists in the valley, in line with international standards, standing at the forefront of the field.

2. Analysis and prediction of siRNA

  It is a kind of double-stranded RNA which is introduced into human body and homologous to endogenous RNA. Through the intervention of siRNA, it can degrade the homologous RNA effectively, so as to know the function of the corresponding gene of the RNA. In addition, siRNA can also target the corresponding gene of the disease and realize the function of gene therapy. The siRNA is effectively predicted by machine learning algorithm, and the corresponding prediction software is developed.

3. Analysis of MicroRNAs and Prediction of Target Genes

  MicroRNA is a small molecule RNA, which is related to the development and disease in the life process. It can inhibit the expression of microRNA at the protein level by targeting the RNA, thus exerting its biological function. At present, the functions of regulating cholesterol dynamic balance, regulating vascular growth and cancer suppression have been proved. In this direction, research has been done on searching for human microRNA of influenza virus and predicting the target genes of microRNA. In this work, we developed a better software for predicting target genes of microRNAs.

4. LncRNA and Tumors

  Through deep learning, artificial intelligence and other new methods to mine the regulatory LncRNA associated with tumors, explain the causes of tumorigenesis, development and regulation, and provide a large data analysis basis for the in-depth study of tumors.