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Translational Biomedical Informatics

Overview of attention for book
Attention for Chapter 5: Informatics for Metabolomics.
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

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12 X users

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Chapter title
Informatics for Metabolomics.
Chapter number 5
Book title
Translational Biomedical Informatics
Published in
Advances in experimental medicine and biology, November 2016
DOI 10.1007/978-981-10-1503-8_5
Pubmed ID
Book ISBNs
978-9-81-101502-1, 978-9-81-101503-8
Authors

Kanthida Kusonmano, Wanwipa Vongsangnak, Pramote Chumnanpuen

Editors

Bairong Shen, Haixu Tang, Xiaoqian Jiang

Abstract

Metabolome profiling of biological systems has the powerful ability to provide the biological understanding of their metabolic functional states responding to the environmental factors or other perturbations. Tons of accumulative metabolomics data have thus been established since pre-metabolomics era. This is directly influenced by the high-throughput analytical techniques, especially mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques. Continuously, the significant numbers of informatics techniques for data processing, statistical analysis, and data mining have been developed. The following tools and databases are advanced for the metabolomics society which provide the useful metabolomics information, e.g., the chemical structures, mass spectrum patterns for peak identification, metabolite profiles, biological functions, dynamic metabolite changes, and biochemical transformations of thousands of small molecules. In this chapter, we aim to introduce overall metabolomics studies from pre- to post-metabolomics era and their impact on society. Directing on post-metabolomics era, we provide a conceptual framework of informatics techniques for metabolomics and show useful examples of techniques, tools, and databases for metabolomics data analysis starting from preprocessing toward functional interpretation. Throughout the framework of informatics techniques for metabolomics provided, it can be further used as a scaffold for translational biomedical research which can thus lead to reveal new metabolite biomarkers, potential metabolic targets, or key metabolic pathways for future disease therapy.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 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 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 1%
Canada 1 1%
Australia 1 1%
Unknown 83 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 16%
Student > Bachelor 14 16%
Student > Ph. D. Student 11 13%
Student > Master 7 8%
Student > Doctoral Student 6 7%
Other 19 22%
Unknown 15 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 17%
Agricultural and Biological Sciences 14 16%
Medicine and Dentistry 9 10%
Chemistry 8 9%
Computer Science 7 8%
Other 13 15%
Unknown 20 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 15 July 2017.
All research outputs
#4,669,241
of 22,899,952 outputs
Outputs from Advances in experimental medicine and biology
#803
of 4,953 outputs
Outputs of similar age
#78,109
of 311,569 outputs
Outputs of similar age from Advances in experimental medicine and biology
#18
of 86 outputs
Altmetric has tracked 22,899,952 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,953 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has done well, scoring higher than 83% 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 311,569 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 86 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.