Chapter title |
Computational Strategies for Biological Interpretation of Metabolomics Data
|
---|---|
Chapter number | 8 |
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_8 |
Pubmed ID | |
Book ISBNs |
978-3-31-947655-1, 978-3-31-947656-8
|
Authors |
Jianguo Xia |
Editors |
Alessandra Sussulini |
Abstract |
Biological interpretation of metabolomics data relies on two basic steps: metabolite identification and functional analysis. These two steps need to be applied in a coordinated manner to enable effective data understanding. The focus of this chapter is to introduce the main computational concepts and workflows during this process. After a general overview of the field, three sections will be presented: the first section will introduce the main computational methods and bioinformatics tools for metabolite identification using spectra from common analytical platforms; the second section will focus on introducing major bioinformatics approaches for functional enrichment analysis of metabolomics data; and the last section will discuss the three main workflows in current metabolomics studies, including the chemometrics approach, the metabolic profiling approach and the more recent chemo-enrichment analysis approach. The chapter ends with summary and future perspectives on computational metabolomics. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Brazil | 1 | 3% |
Unknown | 30 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 9 | 29% |
Student > Master | 4 | 13% |
Student > Doctoral Student | 3 | 10% |
Lecturer | 2 | 6% |
Other | 2 | 6% |
Other | 5 | 16% |
Unknown | 6 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 9 | 29% |
Agricultural and Biological Sciences | 8 | 26% |
Computer Science | 2 | 6% |
Chemistry | 2 | 6% |
Immunology and Microbiology | 1 | 3% |
Other | 2 | 6% |
Unknown | 7 | 23% |