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基于序列信息的两种赖氨酸翻译后修饰位点的预测算法开发

Abstract第3页
中文摘要第5-8页
List of abbreviation第8-10页
Chapter 1 Introduction第10-30页
    1.1 Post-translational modification processes第10-13页
    1.2 Experimental methods for PTM identification第13页
    1.3 Lysine PTM site prediction第13-23页
        1.3.1 The importance of protein lysine PTM sites第15页
        1.3.2 Databases of lysine PTM sites第15-17页
        1.3.3 Feature for the prediction of lysine PTM sites第17-19页
        1.3.4 The algorithm of lysine PTM sites prediction第19-23页
    1.4 Research progress of protein pupylation site prediction第23-26页
        1.4.1 The biological process of pupylation第24页
        1.4.2 The biological function of pupylation第24页
        1.4.3 Databases of pupylation sites第24-25页
        1.4.4 Existing tools for prediction of pupylation sites第25-26页
    1.5 Research progress of protein succinylation site prediction第26-28页
        1.5.1 The biological function of succinylation proteins第27页
        1.5.2 Databases of succinylation sites第27页
        1.5.3 Existing tools for succinylation site prediction第27-28页
    1.6 Article description第28-30页
        1.6.1 Development of protein pupylation sites prediction tool第28页
        1.6.2 Development of protein succinylation sites prediction tool第28-29页
        1.6.3 Introduction of different sections第29-30页
Chapter 2 Prediction of protein pupylation sites based on sequence evolutionaryinformation第30-55页
    2.1 Introduction第30-31页
    2.2 Materials and methods第31-37页
        2.2.1 Data preparation第32-34页
        2.2.2 Encoding scheme of pbCKSAAP第34-35页
        2.2.3 Encoding scheme of CKSAAP第35页
        2.2.4 Feature selection第35-36页
        2.2.5 Model training第36页
        2.2.6 Cross-validation and performance evaluation measurements第36-37页
    2.3 Results and discussion第37-52页
        2.3.1 Performance assessment on the training dataset第37-40页
        2.3.2 Performance comparison of pbPUP with existing predictors第40-44页
        2.3.3 The influence of sequence redundancy on the predictive performance第44-45页
        2.3.4 Comparison of the pbCKSAAP and CKSAAP encoding schemes第45-49页
        2.3.5 Significant features of pbCKSAAP第49-52页
        2.3.6 Web server implementation第52页
    2.4 Summary of chapter 2第52-55页
Chapter 3 Prediction of protein succinylation sites by exploiting amino acid pattern andproperties第55-79页
    3.1 Introduction第55-56页
    3.2 Materials and Methods第56-61页
        3.2.1 Data collection第56-58页
        3.2.2 Feature encoding第58页
        3.2.3 CKSAAP encoding第58页
        3.2.4 Binary encoding第58-59页
        3.2.5 AAindex encoding第59页
        3.2.6 Random forest classifier第59-60页
        3.2.7 Feature selection第60页
        3.2.8 Performance assessment第60页
        3.2.9 Rule extraction第60-61页
    3.3 Results and Discussion第61-76页
        3.3.1 Prediction capabilities of the different encoding features with a RF classifier第61-64页
        3.3.2 A comparison of the proposed SuccinSite with existing methods第64-68页
        3.3.3 Selected informative features第68-74页
        3.3.4 Extracted important rules obtained from the RF models第74页
        3.3.5 Case studies第74-76页
        3.3.6 Online web server第76页
    3.4 Summary of chapter 3第76-79页
Chapter 4 Conclusions and perspectives第79-81页
    4.1 Conclusions第79页
    4.2 Perspectives第79-81页
References第81-94页
Acknowledgements第94-95页
Appendix第95-96页
Curriculum Vitae第96-98页

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