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Metabolomics: From Fundamentals to Clinical Applications

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Attention for Chapter 13: Single-Cell Metabolomics
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Chapter title
Single-Cell Metabolomics
Chapter number 13
Book title
Metabolomics: From Fundamentals to Clinical Applications
Published in
Advances in experimental medicine and biology, January 2017
DOI 10.1007/978-3-319-47656-8_13
Pubmed ID
Book ISBNs
978-3-31-947655-1, 978-3-31-947656-8
Authors

Samy Emara, Sara Amer, Ahmed Ali, Yasmine Abouleila, April Oga, Tsutomu Masujima

Editors

Alessandra Sussulini

Abstract

The dynamics of a cell is always changing. Cells move, divide, communicate, adapt, and are always reacting to their surroundings non-synchronously. Currently, single-cell metabolomics has become the leading field in understanding the phenotypical variations between them, but sample volumes, low analyte concentrations, and validating gentle sample techniques have proven great barriers toward achieving accurate and complete metabolomics profiling. Certainly, advanced technologies such as nanodevices and microfluidic arrays are making great progress, and analytical techniques, such as matrix-assisted laser desorption ionization (MALDI), are gaining popularity with high-throughput methodology. Nevertheless, live single-cell mass spectrometry (LCSMS) values the sample quality and precision, turning once theoretical speculation into present-day applications in a variety of fields, including those of medicine, pharmaceutical, and agricultural industries. While there is still room for much improvement, it is clear that the metabolomics field is progressing toward analysis and discoveries at the single-cell level.

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Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 24%
Researcher 9 16%
Student > Bachelor 4 7%
Professor > Associate Professor 4 7%
Student > Master 4 7%
Other 6 11%
Unknown 15 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 18%
Agricultural and Biological Sciences 10 18%
Chemistry 5 9%
Medicine and Dentistry 4 7%
Chemical Engineering 2 4%
Other 6 11%
Unknown 18 33%