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Algorithmic and artificial intelligence methods for protein bioinformatics /
An in, depth look at the latest research, methods, and applications in the field of protein bioinformatics This book presents the latest developments in protein bioinformatics, introducing for the first time cutting, edge research results alongside novel algorithmic and AI methods for the analysis o...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, N.J. :
J. Wiley & Sons,
©2014.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Cover; Series; Title Page; Copyright; Preface; Contributors; Part I: From Protein Sequence to Structure; Chapter 1: Emphasizing The Role of Proteins in Construction of the Developmental Genetic Toolkit in Plants; 1.1 Introduction; 1.2 Evolutionary Developmental (Evo-Devo) Roles in Embryogenesis of Plants (in Developmental Plant Genetic Toolkit Formation); 1.3 Phases in Embryogenesis in Arabidopsis Thaliana; 1.4 Analysis; 1.5 Conclusions; References; Bibliography; Chapter 2: Protein Sequence Motif Information Discovery; 2.1 Introduction; 2.2 Granule Computing Approaches; 2.3 Experimental Setup.
- 2.4 Protein Sequence Motif Information Discovered by FGK ModelReferences; Chapter 3: Identifying Calcium Binding Sites in Proteins; 3.1 Introduction; 3.2 Methods; 3.3 Results and Discussion; 3.4 Conclusion; References; Chapter 4: Review of Imbalanced Data Learning for Protein Methylation Prediction; 4.1 Introduction; 4.2 Protein and Methylation; 4.3 Related Works on Methylation Prediction; 4.4 Conclusion; Acknowledgments; References; Chapter 5: Analysis and Prediction of Protein Posttranslational Modification Sites; 5.1 Introduction; 5.2 Musite: A Machine Learning Approach.
- 5.3 Musite Implementation5.4 Summary; Acknowledgments; References; Part II: Protein Analysis and Prediction; Chapter 6: Protein Local Structure Prediction; 6.1 Introduction; 6.2 Structural Cluster Approach; 6.3 Sequence Cluster Approach; 6.4 Support Vector Machines for Local Protein Structure Prediction; 6.5 Clustering Support Vector Machines for Local Protein Structure Prediction; 6.6 Experimental Results; References; Chapter 7: Protein Structural Boundary Prediction; 7.1 Introduction; 7.2 Background; 7.3 New Binary Classifiers for Protein Structural Boundary Prediction; 7.4 Conclusion.
- 9.4 Experimental Results9.5 Conclusions and Future Directions; Acknowledgments; References; Chapter 10: Protein Contact Order Prediction: Update; 10.1 Introduction; 10.2 Correlated protein properties; 10.3 Other contact measurements; 10.4 Contact order calculation; 10.5 Contact order prediction by homology; 10.6 Contact order prediction from sequence; 10.7 The public contact order web server; 10.8 Conclusions; References; Chapter 11: Progress in Prediction of Oxidation States of Cysteines via Computational Approaches; 11.1 Introduction.