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Statistical Genomics

Overview of attention for book
Cover of 'Statistical Genomics'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Multi-omics Data Deconvolution and Integration: New Methods, Insights, and Translational Implications
  3. Altmetric Badge
    Chapter 2 Statistical and Machine Learning Methods for Discovering Prognostic Biomarkers for Survival Outcomes
  4. Altmetric Badge
    Chapter 3 Cell-Type Deconvolution of Bulk DNA Methylation Data with EpiSCORE
  5. Altmetric Badge
    Chapter 4 Profiling Cellular Ecosystems at Single-Cell Resolution and at Scale with EcoTyper
  6. Altmetric Badge
    Chapter 5 Statistical Methods for Integrative Clustering of Multi-omics Data
  7. Altmetric Badge
    Chapter 6 Analysis of Single-Cell RNA-seq Data
  8. Altmetric Badge
    Chapter 7 A Primer on Preprocessing, Visualization, Clustering, and Phenotyping of Barcode-Based Spatial Transcriptomics Data
  9. Altmetric Badge
    Chapter 8 Statistical Analysis of Multiplex Immunofluorescence and Immunohistochemistry Imaging Data
  10. Altmetric Badge
    Chapter 9 Statistical Analysis in ChIP-seq-Related Applications
  11. Altmetric Badge
    Chapter 10 Bioinformatic and Statistical Analysis of Microbiome Data
  12. Altmetric Badge
    Chapter 11 Statistical and Computational Methods for Microbial Strain Analysis
  13. Altmetric Badge
    Chapter 12 Statistics and Machine Learning in Mass Spectrometry-Based Metabolomics Analysis
  14. Altmetric Badge
    Chapter 13 Statistical and Computational Methods for Proteogenomic Data Analysis
  15. Altmetric Badge
    Chapter 14 Pharmacogenomic and Statistical Analysis
  16. Altmetric Badge
    Chapter 15 Statistical Methods for Disease Risk Prediction with Genotype Data
  17. Altmetric Badge
    Chapter 16 Statistical Methods Inspired by Challenges in Pediatric Cancer Multi-omics
Attention for Chapter 11: Statistical and Computational Methods for Microbial Strain Analysis
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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 (86th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

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17 X users

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2 Mendeley
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Chapter title
Statistical and Computational Methods for Microbial Strain Analysis
Chapter number 11
Book title
Statistical Genomics
Published in
Methods in molecular biology, December 2022
DOI 10.1007/978-1-0716-2986-4_11
Pubmed ID
Book ISBNs
978-1-07-162985-7, 978-1-07-162986-4
Authors

Ma, Siyuan, Li, Hongzhe, Siyuan Ma, Hongzhe Li

X Demographics

X Demographics

The data shown below were collected from the profiles of 17 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 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 50%
Researcher 1 50%
Student > Master 1 50%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 50%
Agricultural and Biological Sciences 1 50%
Engineering 1 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 19 March 2023.
All research outputs
#3,149,347
of 25,214,112 outputs
Outputs from Methods in molecular biology
#601
of 14,142 outputs
Outputs of similar age
#64,282
of 485,225 outputs
Outputs of similar age from Methods in molecular biology
#16
of 752 outputs
Altmetric has tracked 25,214,112 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,142 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done particularly well, scoring higher than 95% 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 485,225 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 86% of its contemporaries.
We're also able to compare this research output to 752 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 98% of its contemporaries.