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  • Produktbild: Computational Immunology
  • Produktbild: Computational Immunology

Computational Immunology Models and Tools

139,99 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

27.10.2015

Verlag

Elsevier Science & Technology

Seitenzahl

212

Maße (L/B/H)

22,8/14,9/1,2 cm

Gewicht

357 g

Sprache

Englisch

ISBN

978-0-12-803697-6

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

27.10.2015

Verlag

Elsevier Science & Technology

Seitenzahl

212

Maße (L/B/H)

22,8/14,9/1,2 cm

Gewicht

357 g

Sprache

Englisch

ISBN

978-0-12-803697-6

EU-Ansprechpartner

Zeitfracht Medien GmbH
Ferdinand-Jühlke-Straße 7
99095 Erfurt
DE
produktsicherheit@zeitfracht.de

Herstelleradresse

Elsevier Science & Technology
125 London Wall
EC2Y 5AS London
GB
tradeorders@elsevier.com

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Die Leseprobe wird geladen.
  • Produktbild: Computational Immunology
  • Produktbild: Computational Immunology

  • 1. Introduction to Computational Immunology

    Overview

    Modeling tools and techniques

    Use Cases Illustrating the Application of Computational Immunology Technologies

    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

      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

        4. Immunoinformatics cybernfrastructure 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 (CINET)

        Pathosystems Resource Integration Center (Patric)

        Clinical Data Integration

        Concluding Remarks

        5. Ordinary Differential Equations (ODE) based Modeling

        Introduction

        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

          6. Agent-Based Modeling and High Performance Computing

          Introduction and basic definitions

          Related work

          Technical implementation of ENISI

          Formal Representation of ENISI

          Agent Based Modeling using ENISI

          Calibration and validation of the preliminary model

          Sensitivity Analysis for ABM

          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

            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

              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 (ARIANA)
              • Case study: Reconstructing the Th17 differentiation networkConcluding remarks

                • 8. Multiscale Modeling: Concepts, Technologies, and Use Cases in Immunology

                Introduction

                Multiscale modeling concepts and techniques

                • Modeling Technologies and Tools
                • From Single Scale to Multiscale Modeling

                  Sensitivity analysis

                  • Global versus local sensitivity analysis
                  • Sparse experimental design for sensitivity analysis
                  • Temporal significance of modeling parameters
                  • Sensitivity analysis across scales

                    Multiscale Modeling of Mucosal Immune Responses

                    • The scales of ENISI platform
                    • Challenges and opportunities

                      Case Study

                      • Modeling mucosal immunity in the Gut
                      • Multiscale modeling of mucosal immune responses

                        Concluding remarks

                        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