信息分析中的化学计量学和生物信息学新方法分析——基于支持向量机 小波变换 傅里叶变换 分子对接 动力学模拟的化学和生物信息分析-analysis of new chemometrics and bioinformatics methods in information analysis - chemical and biological information analysis based on support vector machine.docxVIP

AbstractToday’s information age is characterized by the fast development and wide penetration of information science. As the new interdisciplinary subjects in the areas of chemistry, biology, informatics, computer science, mathematics and physics, all of the methodologies of chemometrics and bioinformatics have shown great vitality in the analytical area of tremendous data in the Post-genomic Era. Their studying contents are nearly related to all of the informatics analysis areas such as control, measure, capture, analysis, management and application. Although they have tremendously contributed to scientific studies, the continuous development of information science still make the researchers continuously apply them and develop new research methods and tools to deal with and extract their valuable information.This dissertation mainly aims at the complex information in the chemical and biological areas, based on some methods like the Wavelet Transform (WT), the Support Vector Machine (SVM) and the Fourier Transform (FT) to study the following contents: 1. The interaction between antibiotics and DNAs; 2. The application of frequency analytical method which is based on WT in analyzing the chemical oscillating systems and gene sequence; 3. Wangzaozin A’s inducing cancer apoptosis and its protein targets; 4. The application of chemometrics in dealing with electrochemical signals. The detailed contents are as follows:The interaction between antibiotics and DNAsBased on the Support Vector Machine, the Best Prediction Set SVM is constructed to study the interaction between antibiotics and DNAs. By using the thirty experimental data and twenty-four molecular structural quantitative parameters, this method predicts the interaction between antibiotics and DNAs and analyzes the main parameters which affect their interactive modes. The results show that five parameters among these twenty-four are main parameters which decide the interaction between antibiotics and DNAs, and the