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Host-Pathogen Interactions

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Cover of 'Host-Pathogen Interactions'

Table of Contents

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    Book Overview
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    Chapter 1 Genetic Association Studies in Host–Pathogen Interaction Analysis
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    Chapter 2 Bacterial Genotyping Methods: From the Basics to Modern
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    Chapter 3 Real-Time Reverse Transcription PCR as a Tool to Study Virulence Gene Regulation in Bacterial Pathogens
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    Chapter 4 Usage of a Bioluminescence Reporter System to Image Promoter Activity During Host Infection
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    Chapter 5 lacZ Reporter System as a Tool to Study Virulence Gene Regulation in Bacterial Pathogens
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    Chapter 6 Western Blotting Against Tagged Virulence Determinants to Study Bacterial Pathogenicity
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    Chapter 7 Molecular Methods to Analyze the Effect of Proteins Expressed by Salmonella During Its Intracellular Stage
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    Chapter 8 Organoids as a Model to Study Infectious Disease
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    Chapter 9 Surface Proteome Biotinylation Combined with Bioinformatic Tools as a Strategy for Predicting Pathogen Interacting Proteins
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    Chapter 10 Systems Biology Modeling to Study Pathogen–Host Interactions
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    Chapter 11 Phage Therapy: Various Perspectives on How to Improve the Art
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    Chapter 12 Application of RNA-seq and Bioimaging Methods to Study Microbe–Microbe Interactions and Their Effects on Biofilm Formation and Gene Expression
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    Chapter 13 Serial Dilution-Based Growth Curves and Growth Curve Synchronization for High-Resolution Time Series of Bacterial Biofilm Growth
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    Chapter 14 Detection of Bacterial Quorum Sensing Molecules
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    Chapter 15 Generating Chromosome-Located Transcriptional Fusions to Fluorescent Proteins for Single-Cell Gene Expression Analysis in Pseudomonas syringae
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    Chapter 16 Introduction of Genetic Material in Ralstonia solanacearum Through Natural Transformation and Conjugation
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    Chapter 17 In Vitro and In Vivo Secretion/Translocation Assays to Identify Novel Ralstonia solanacearum Type 3 Effectors
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    Chapter 18 Plant Pathogenicity Phenotyping of Ralstonia solanacearum Strains
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    Chapter 19 Methods to Quantify Biotic-Induced Stress in Plants
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    Chapter 20 From Sample to Data: Preparing, Obtaining, and Analyzing Images of Plant-Pathogen Interactions Using Confocal Microscopy
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    Chapter 21 Screening of c-di-GMP-Regulated Exopolysaccharides in Host Interacting Bacteria
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    Chapter 22 Primary Characterization of Small RNAs in Symbiotic Nitrogen-Fixing Bacteria
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    Chapter 23 A New, Nondestructive, Split-Root System for Local and Systemic Plant Responses Studies with Soybean
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    Chapter 24 Methods for the Characterization of Plant-Growth Promoting Rhizobacteria
Attention for Chapter 10: Systems Biology Modeling to Study Pathogen–Host Interactions
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Chapter title
Systems Biology Modeling to Study Pathogen–Host Interactions
Chapter number 10
Book title
Host-Pathogen Interactions
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7604-1_10
Pubmed ID
Book ISBNs
978-1-4939-7603-4, 978-1-4939-7604-1
Authors

Müberra Fatma Cesur, Saliha Durmuş

Abstract

Pathogen-host interactions (PHIs) underlie the process of infection. The systems biology view of the whole PHI system is superior to the investigation of the pathogen or host separately in understanding the infection mechanisms. Especially, the identification of host-oriented drug targets for the next-generation anti-infection therapeutics requires the properties of the host factors targeted by pathogens. Here, we provide an outline of computational analysis of PHI networks, focusing on the properties of the pathogen-targeted host proteins. We also provide information about the available PHI data and the related Web-based resources.

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 27%
Student > Ph. D. Student 3 27%
Student > Bachelor 1 9%
Student > Doctoral Student 1 9%
Lecturer 1 9%
Other 2 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 36%
Computer Science 2 18%
Immunology and Microbiology 1 9%
Agricultural and Biological Sciences 1 9%
Social Sciences 1 9%
Other 2 18%