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Computational immunology : models and tools /
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London, UK :
Academic Press is an imprint of Elsevier,
[2015]
|
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Front Cover
- Computational Immunology: Models and Tools
- Copyright Page
- Contents
- List of Contributors
- 1 Introduction to Computational Immunology
- Overview
- Modeling Tools and Techniques
- Use Cases Illustrating the Application of Computational Immunology Technologies
- Acknowledgments
- References
- 2 Computational Modeling
- Overview on Computational Modeling
- Translational Research Iterative Modeling Cycle
- Information and Knowledge Extraction from the Literature
- Collect New Data and Data from Public Repositories
- Model Development
- In Silico Experimentation
- Validation of Computational Hypotheses and New Knowledge
- Considerations on Computational Modeling Technologies
- Computational Modeling Tools for Immunology and Infectious Disease Research
- Concluding Remarks
- Acknowledgments
- References
- 3 Use of Computational Modeling in Immunological Research
- Introduction
- Computational and Mathematical Modeling of the Immune Response to Helicobacter pylori
- Inflammatory Bowel Disease
- ODE Model of CD4+ T-Cell Differentiation
- T Follicular Helper Cell Differentiation
- Concluding Remarks
- Acknowledgments
- References
- 4 Immunoinformatics Cyberinfrastructure for Modeling and Analytics
- Introduction
- Web Portal
- LabKey-Based Laboratory Information Management System
- Public Repositories: ImmPort
- Global Gene Expression Analysis
- High-Performance Computing Environment
- HPC Infrastructure for ENISI MSM Modeling
- CyberInfrastructure for NETwork Science
- Pathosystems Resource Integration Center
- Clinical Data Integration
- Concluding Remarks
- Acknowledgments
- Appendix: MIEP Data Uploaded to ImmPort
- References
- 5 Ordinary Differential Equations (ODEs) Based Modeling
- Introduction
- Modeling Network of Gene Regulation
- Modeling Signaling Pathways.
- Modeling Biochemical Reaction Networks
- Modeling Multiple Scales
- ODE-Based Modeling Pipeline
- Model Development
- Model Calibration
- Deterministic Simulations
- Sensitivity Analysis
- Model-Driven Hypothesis Generation
- Case Studies: CD4+ T-Cell Differentiation Model
- Concluding Remarks
- Acknowledgments
- References
- 6 Agent-Based Modeling and High Performance Computing
- Introduction and Basic Definitions
- Related Work
- Technical Implementation of ENISI
- Formal Representation of ENISI
- Interaction-Based Approach for Modeling Gut Mucosa: Coevolving Graphical Discrete Dynamical Systems (CGDDS)
- Modeling Immune System using CGDDS
- Agent-Based Modeling Using ENISI
- ENISI HPC Implementation
- ABM of H. pylori
- Calibration and Validation of the Preliminary Model
- Sensitivity Analysis for ABM
- Influence of Parameters
- Ranking of Parameters
- Quantifying Uncertainty
- Scaling the Sensitivity Analysis Calculations
- Scalability and Performance
- Modeling Study Investigating Immune Responses to H. pylori
- Use Case: Predictive Computational Modeling of the Mucosal Immune Responses During H. pylori Infection
- Concluding Remarks
- Acknowledgment
- References
- 7 From Big Data Analytics and Network Inference to Systems Modeling
- Introduction
- Big Bata Drives Big Models
- Experimental Planning and Power Analysis
- RNA-Seq Analysis Pipeline
- Read Summarization
- Differential Expression Analysis
- Time Series Data
- Unsupervised High-Resolution Clustering
- Supervised Multistage Clustering to Cluster Genes Based on Pattern of Expression
- Tools, Techniques, and Pipelines
- RNA-Seq Analysis in the Cloud
- RNA Rocket at the PAThosystems Resource Integration Center
- Network Inference and Analytics
- Supervised Machine Learning Methods
- NetGenerator.
- Adaptive Robust Integrative Analysis for Finding Novel Association
- Case Study: Reconstructing the Th17 Differentiation Network
- Concluding Remarks
- Acknowledgments
- References
- 8 Multiscale Modeling: Concepts, Technologies, and Use Cases in Immunology
- Introduction
- MSM Concepts and Techniques
- Modeling Technologies and Tools
- From Single Scale to MSM
- Sensitivity Analysis
- Global versus Local SA
- Sparse Experimental Design for SA
- Temporal Significance of Modeling Parameters
- SA Across Scales
- MSM of Mucosal Immune Responses
- The Scales of ENISI Platform
- Challenges and Opportunities
- OO Design
- Performance Matching
- HPC-Driven MSM of Mucosal Immune Responses
- Future of MSM
- Case Study
- Modeling Mucosal Immunity in the Gut
- Multiscale Model for IBD
- The Intracellular Scale
- The Intercellular Scale
- The Cellular Scale
- Model Settings
- Simulation
- MSM of Mucosal Immune Responses
- Concluding Remarks
- Acknowledgment
- References
- 9 Modeling Exercises
- Modeling Tools
- Models
- Computational Model of Immune Responses to Clostridium difficile Infection
- Computational Model of the 3-Node T Helper Type 17 Model
- Computational Model of the 9-Node Th1/Th17/Treg Model
- Model Complexity and Model-Driven Hypothesis Generation
- Concluding Remarks
- Acknowledgment
- References
- Back Cover.