de
en
Schliessen
Detailsuche
Bibliotheken
Projekt
Impressum
Datenschutz
zum Inhalt
Detailsuche
Schnellsuche:
OK
Ergebnisliste
Titel
Titel
Inhalt
Inhalt
Seite
Seite
Im Dokument suchen
Plötz, Thomas: Advanced stochastic protein sequence analysis. 2005
Inhalt
Contents
Introduction
Principles of Modern Protein Analysis
The Central Dogma of Molecular Biology
Proteins: The Fundamentals of Life
Biochemical Composition
Biological Relevancy
Protein Relationships
Protein Families
Exemplary Hierarchical Classification
Protein Analysis
The Drug Discovery Process
Protein Sequence Analysis
Summary
Computational Protein Sequence Analysis
Pairwise Sequence Alignment
Principles of Sequence Alignment
Heuristic Approximations
Analysis of Sequence Families
Profile Analysis
Profile Hidden Markov Models
Further Probabilistic Modeling Approaches
Signal Processing based Sequence Comparison
Alternative Representations of Protein Sequences
Signal Processing Methods for Classification
Summary
Concepts for Improved HMM Based Sequence Analysis
Assessment of Current Methodologies' Capabilities
Task: Homology Detection at the Superfamily Level
Capabilities of State-of-the-Art Approaches
Improving the Quality of HMM Based Sequence Analysis
Semi-Continuous Feature Based Modeling
Model Architectures with Reduced Complexity
Accelerating the Model Evaluation
Summary
Advanced Probabilistic Models for Protein Families
Feature Extraction from Protein Sequences
Rich Signal-Like Protein Sequence Representation
Feature Extraction by Abstraction
Robust Feature Based Profile HMMs and Remote Homology Detection
Feature Space Representation
General Semi-Continuous Profile HMMs
Specialization by Adaptation
Explicit Background Model
Protein Family HMMs with Reduced Complexity
Beyond Profile HMMs
Protein Family Modeling using Sub-Protein Units (SPUs)
Accelerating the Model Evaluation by Pruning Techniques
State-Space Pruning
Combined Model Evaluation
Optimization of Mixture Density Evaluation
Summary
Evaluation
Methodology and Datasets
Effectiveness of Semi-Continuous Feature Based Profile HMMs
Advanced Stochastic Protein Family Models for Small Training Sets
Effectiveness of Sub-Protein Unit based Models
Effectiveness of Bounded Left-Right Models
Acceleration of Protein Family HMM Evaluation
Effectiveness of State-Space Pruning
Effectiveness of Accelerated Mixture Density Evaluation
Combined Evaluation of Advanced Stochastic Modeling Techniques
Summary
Conclusion
Wavelets
Fourier Analysis
Continuous Wavelet Transformation
Discrete Wavelet Transformation
Principal Components Analysis (PCA)
Amino Acid Indices
Detailed Evaluation Results
Bibliography