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Plant-Pathogen Interactions

Overview of attention for book
Cover of 'Plant-Pathogen Interactions'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Galaxy as a platform for identifying candidate pathogen effectors.
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    Chapter 2 Bioinformatic analysis of expression data to identify effector candidates.
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    Chapter 3 Two-Dimensional Data Binning for the Analysis of Genome Architecture in Filamentous Plant Pathogens and Other Eukaryotes
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    Chapter 4 On the statistics of identifying candidate pathogen effectors.
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    Chapter 5 High-Throughput Imaging of Plant Immune Responses
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    Chapter 6 In Vivo Protein-Protein Interaction Studies with BiFC: Conditions, Cautions, and Caveats.
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    Chapter 7 Particle bombardment-mediated transient expression to identify localization signals in plant disease resistance proteins and target sites for the proteolytic activity of pathogen effectors.
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    Chapter 8 Purification of Fungal Haustoria from Infected Plant Tissue by Flow Cytometry
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    Chapter 9 Functional characterization of nematode effectors in plants.
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    Chapter 10 Silencing of Aphid Genes by Feeding on Stable Transgenic Arabidopsis thaliana.
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    Chapter 11 Leaf-Disc Assay Based on Transient Over-Expression in Nicotiana benthamiana to Allow Functional Screening of Candidate Effectors from Aphids.
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    Chapter 12 A Growth Quantification Assay for Hyaloperonospora arabidopsidis Isolates in Arabidopsis thaliana
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    Chapter 13 Simple Quantification of In Planta Fungal Biomass
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    Chapter 14 Virus-Induced Gene Silencing and Agrobacterium tumefaciens-Mediated Transient Expression in Nicotiana tabacum
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    Chapter 15 DIGE-ABPP by Click Chemistry: Pairwise Comparison of Serine Hydrolase Activities from the Apoplast of Infected Plants.
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    Chapter 16 A Simple and Fast Protocol for the Protein Complex Immunoprecipitation (Co-IP) of Effector: Host Protein Complexes
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    Chapter 17 An Arabidopsis and Tomato Mesophyll Protoplast System for Fast Identification of Early MAMP-Triggered Immunity-Suppressing Effectors
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    Chapter 18 Production of RXLR Effector Proteins for Structural Analysis by X-Ray Crystallography
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    Chapter 19 The Do's and Don'ts of Effectoromics.
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    Chapter 20 Protoplast Cell Death Assay to Study Magnaporthe oryzae AVR Gene Function in Rice
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    Chapter 21 A Bacterial Type III Secretion-Based Delivery System for Functional Assays of Fungal Effectors in Cereals
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    Chapter 22 Genomic DNA Library Preparation for Resistance Gene Enrichment and Sequencing (RenSeq) in Plants.
Attention for Chapter 1: Galaxy as a platform for identifying candidate pathogen effectors.
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About this Attention Score

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  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

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Citations

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6 Dimensions

Readers on

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12 Mendeley
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2 CiteULike
Summary X Dimensions citations
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Chapter title
Galaxy as a platform for identifying candidate pathogen effectors.
Chapter number 1
Book title
Plant-Pathogen Interactions
Published in
Methods in molecular biology, January 2014
DOI 10.1007/978-1-62703-986-4_1
Pubmed ID
24643548
Book ISBNs
978-1-62703-985-7, 978-1-62703-986-4
Authors

Peter J. A. Cock, Leighton Pritchard, Cock PJ, Pritchard L, Cock, Peter J. A., Pritchard, Leighton

Abstract

The Galaxy web platform provides an integrated system for its users to run multiple computational tools, linking their output in order to perform sophisticated analysis without requiring any programming or installation of software beyond a modern web-browser. Analyses can be saved as reusable workflows, and shared with other Galaxy users, allowing them to easily perform the same analysis or protocol on their own data.We describe example Galaxy workflows for the identification of candidate pathogen effector proteins. Our main example focuses on nematode plant pathogens where signal peptide and transmembrane prediction tools are used to identify predicted secreted proteins.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 1 8%
Unknown 11 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 50%
Professor > Associate Professor 2 17%
Other 2 17%
Unknown 2 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 25%
Computer Science 3 25%
Biochemistry, Genetics and Molecular Biology 2 17%
Business, Management and Accounting 1 8%
Medicine and Dentistry 1 8%
Other 0 0%
Unknown 2 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 October 2018.
All research outputs
#13,406,705
of 22,751,628 outputs
Outputs from Methods in molecular biology
#3,603
of 13,088 outputs
Outputs of similar age
#163,226
of 305,229 outputs
Outputs of similar age from Methods in molecular biology
#149
of 597 outputs
Altmetric has tracked 22,751,628 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,088 research outputs from this source. They receive a mean Attention Score of 3.3. This one has gotten more attention than average, scoring higher than 70% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 305,229 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 597 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.

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