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Plant Chemical Genomics

Overview of attention for book
Cover of 'Plant Chemical Genomics'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Multi-Parametric Screening in Arabidopsis thaliana Seedlings
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    Chapter 2 Novel Micro-Phenotyping Approach to Chemical Genetic Screening for Increased Plant Tolerance to Abiotic Stress
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    Chapter 3 Method for Ultrarapid High-Content Screening for Biologically Active Chemicals Using Plant Pollen
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    Chapter 4 A High-Throughput Chemical Screening Method for Inhibitors and Potentiators of Hypersensitive Cell Death Using Suspension Cell Culture of Arabidopsis thaliana
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    Chapter 5 High-Throughput Screening of Chemical Compound Libraries for Modulators of Salicylic Acid Signaling by In Situ Monitoring of Glucuronidase-Based Reporter Gene Expression
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    Chapter 6 Identification of Chemical Inducers of the Phosphate-Starvation Signaling Pathway in A. thaliana Using Chemical Genetics
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    Chapter 7 Phenotype-Based Screening of Small Molecules to Modify Plant Cell Walls Using BY-2 Cells
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    Chapter 8 Small-Molecule Screening to Increase Agrobacterium -Mediated Transformation Efficiency in Legumes
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    Chapter 9 High-Throughput In Vitro Screening for Inhibitors of Cereal α-Glucosidase
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    Chapter 10 Chemical Screening for Strigolactone Receptor Antagonists Using Arabidopsis thaliana
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    Chapter 11 Chemical Control of ABA Receptors to Enable Plant Protection Against Water Stress
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    Chapter 12 Modes of Action Study of Seed Germination Inhibitor Germostatin by Forward Genetics Screening
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    Chapter 13 Enantiodifferential Approach for the Target Protein Detection of the Jasmonate Glucoside That Controls the Leaf Closure of Samanea saman
  15. Altmetric Badge
    Chapter 14 Using the QCM Biosensor-Based T7 Phage Display Combined with Bioinformatics Analysis for Target Identification of Bioactive Small Molecule
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    Chapter 15 Genomic Identification and Analysis of Specialized Metabolite Biosynthetic Gene Clusters in Plants Using PlantiSMASH
  17. Altmetric Badge
    Chapter 16 Chemical Genomics Translatability from Unicellular to Multicellular Models
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    Chapter 17 Chemical Screening for Flagella-Associated Phenotypes in Chlamydomonas reinhardtii
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    Chapter 18 FnCpf1-Mediated Targeted Mutagenesis in Plants
  20. Altmetric Badge
    Chapter 19 Erratum to: Chemical Screening for Flagella-Associated Phenotypes in Chlamydomonas reinhardtii
Attention for Chapter 15: Genomic Identification and Analysis of Specialized Metabolite Biosynthetic Gene Clusters in Plants Using PlantiSMASH
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

blogs
1 blog
twitter
8 tweeters

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
30 Mendeley
Summary Blogs Twitter Dimensions citations
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Chapter title
Genomic Identification and Analysis of Specialized Metabolite Biosynthetic Gene Clusters in Plants Using PlantiSMASH
Chapter number 15
Book title
Plant Chemical Genomics
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7874-8_15
Pubmed ID
29846928
Book ISBNs
978-1-4939-7873-1, 978-1-4939-7874-8
Authors

Satria A. Kautsar, Hernando G. Suarez Duran, Marnix H. Medema, Kautsar, Satria A., Suarez Duran, Hernando G., Medema, Marnix H.

Abstract

Plants produce a vast diversity of specialized metabolites, which play important roles in the interactions with their microbiome, as well as with animals and other plants. Many such molecules have valuable biological activities that render them (potentially) useful as medicines, flavors and fragrances, nutritional ingredients, or cosmetics. Recently, plant scientists have discovered that the genes for many biosynthetic pathways for the production of such specialized metabolites are physically clustered on the chromosome within biosynthetic gene clusters (BGCs). The Plant Secondary Metabolite Analysis Shell (plantiSMASH) allows for the automated identification of such plant BGCs, facilitates comparison of BGCs across genomes, and helps users to predict the functional interactions of pairs of genes within and between BGCs based on coexpression analysis. In this chapter, we provide a detailed protocol on how to install and run plantiSMASH, and how to interpret its results to draw biological conclusions that are supported by the data.

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Twitter Demographics

The data shown below were collected from the profiles of 8 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 30%
Researcher 5 17%
Student > Master 4 13%
Student > Doctoral Student 2 7%
Student > Postgraduate 2 7%
Other 3 10%
Unknown 5 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 37%
Agricultural and Biological Sciences 9 30%
Unspecified 1 3%
Chemistry 1 3%
Medicine and Dentistry 1 3%
Other 0 0%
Unknown 7 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 05 June 2018.
All research outputs
#2,729,784
of 23,083,773 outputs
Outputs from Methods in molecular biology
#511
of 13,205 outputs
Outputs of similar age
#63,707
of 442,614 outputs
Outputs of similar age from Methods in molecular biology
#31
of 1,499 outputs
Altmetric has tracked 23,083,773 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,205 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done particularly well, scoring higher than 96% 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 442,614 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 1,499 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.

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