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Mendeley readers
Chapter title |
Metabolomic Bioinformatic Analysis
|
---|---|
Chapter number | 22 |
Book title |
Molecular Profiling
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-6990-6_22 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6989-0, 978-1-4939-6990-6
|
Authors |
Allyson L. Dailey |
Editors |
Virginia Espina |
Abstract |
Metabolomics allows for the investigation of the small molecules found within living systems. Based on the design of the experiments, it is not uncommon for these analyses to include matrices of thousands of variables. In order to handle such large datasets, many have turned to multivariate statistical analyses to analyze and understand their data. Herein, we present protocols for using R to analyze metabolomic data using some of the more common multivariate statistical techniques. |
Mendeley readers
The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 8 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Unspecified | 1 | 13% |
Lecturer | 1 | 13% |
Student > Doctoral Student | 1 | 13% |
Lecturer > Senior Lecturer | 1 | 13% |
Unknown | 4 | 50% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 2 | 25% |
Unspecified | 1 | 13% |
Medicine and Dentistry | 1 | 13% |
Unknown | 4 | 50% |