COVID-19 Update: We are currently shipping orders daily. However, due to transit disruptions in some geographies, deliveries may be delayed. To provide all customers with timely access to content, we are offering 50% off Science and Technology Print & eBook bundle options. Terms & conditions.
Metabolomics Perspectives - 1st Edition - ISBN: 9780323850629

Metabolomics Perspectives

1st Edition

From Theory to Practical Application

Editor: Jacopo Troisi
Paperback ISBN: 9780323850629
Imprint: Academic Press
Published Date: 15th January 2022
Page Count: 528
Sales tax will be calculated at check-out Price includes VAT/GST

Institutional Subscription

Secure Checkout

Personal information is secured with SSL technology.

Free Shipping

Free global shipping
No minimum order.

Description

Metabolomics Perspectives: From Theory to Practical Application provides a thorough overview of metabolomics fundamentals, techniques, data analytics approaches, and their direct applications in the life sciences, medicine and industry. The book begins with metabolomic profiling methods and data analysis approaches, followed by descriptions and guidance for applying metabolomics in biomedicine, drug discovery, public health, precision medicine, plant, food science, agriculture, and cell biology and microbiology, among other disciplines. In addition, methods and protocol instructions are provided on experimental design, mass spectrometry, NMR, neonatal screening, metabolomics standardization, and metabolomic profiling in life science research and biomarker discovery.

Guidance in network analysis, use of R codes, univariate analysis, square discriminant analysis, random forest, support vectoral machine, artificial neural network, ensembling, and genetic algorithms is also included. Finally, the book features a pool of specifically designed commented codes (R scripts) and several sets of metabolomics data that is hosted on a companion website.

Key Features

  • Describes metabolomics approaches across a range of applications, including life science and biomedical research, drug discovery, food and agriculture and microbiology
  • Features chapter contributions from international leaders in the field
  • Includes commented codes (R scripts) and several sets of metabolomics data hosted on a companion website

Readership

Life science researchers in biochemistry, molecular biology, or cell biology; systems biology researchers; medical and health informaticists; clinical chemists and pharmaceutical scientists; analytical chemists. Clinicians and students

Table of Contents

Part I – Fundamentals
1. System Biology (Sean Richards – University of Tennessee – USA)
a. Introduction
b. Genomics
c. Epigenomics
d. Transcriptomics
e. Proteomics
f. Metabolomics
2. Mass spectrometry in metabolomics (Ray Kruse Iles – Abu Dhabi University - Arabic Emirates)
3. NMR in metabolomics (Raja Roy – Centre of Biomedical Research: Lucknow India)
4. Targeted metabolomics (Margherita Ruoppolo – University of Naples “Federico II” – Italy)
a. Neonatal screening
5. Untargeted metabolomics (Jacopo Troisi – University of Naples – Italy)
a. Metabolome extraction and purification methodologies
b. Metabolomics standardization reporting proposal
c. Spectra deconvolution and annotation
d. Local and non-local metabolomics effects
e. Metabolomic profiling
f. Biomarkers discovery
g. Network analysis

Part II – Data analysis
6. Data pretreatment (Marco Calderisi – Kode srl – Italy)
a. Signals Alignment
b. Normalization
c. Scaling
d. Commented R codes examples
7. Univariate analysis (Elisabetta Marras – University of Cagliari – Italy)
a. Fold Change
b. Data distributions
c. Parametric and non-parametrical statistical tests
d. Analysis of Variance (ANOVA)
e. Post hoc testing
f. Study design, power analysis and sample size
g. Commented R codes examples
8. Machine Learning approach in Metabolomics (Jasmine Chong - McGill University - Canada)
a. Unsupervised learning
i. Clustering
ii. Principal Component Analysis
iii. K-means
b. Supervised learning
i. Partial Least Square Discriminant Analysis
ii. Random Forest
iii. Support Vectoral Machine
iv. k-nearest neighbors
v. Artificial Neural Network
c. Ensembling
d. Commented R codes examples
9. Metabolites selection (Usman Qamar – National University of Sciences and Technology, Islamabad – Pakistan)
a. PLS-DA VIP-score
b. Genetic algorithms
c. Means Decrease Accuracy
d. Commented R codes examples
10. Pathway analysis (Ron Caspi – SRI International – USA)
11. Metabolomics derived omics (Sonia Cortassa - Johns Hopkins University School of Medicine, Baltimore, Maryland - USA)
a. Lipidomics
b. Fluxomics
c. Exposomics

Part III – Application
12. Plant Metabolomics (Ian Dubery - University of Johannesburg - South Africa)
13. Cell culture metabolomics (Anna Halama – Weill Cornell Medicine in Qatar, Doha – Qatar)
14. Microbial metabolomics (Sarina Claassens - Unit for Environmental Sciences and Management, North‐West University, Potchefstroom - South Africa)
15. Food metabolomics (Joachim Kopka - Max-Planck-Institute of Molecular Plant Physiology, Department of Molecular Physiology: Applied Metabolome Analysis, Potsdam-Golm - Germany)
16. Metabolomics application in animal science (S. Tomonaga – Kyoto University, Japan)
17. Single cell metabolomics (Renato Zenobi – Swiss Federal Institute of Technology in Zurich – Switzerland)
18. Mass spectrometry imaging: the metabolomics visualization (B. Balluff - Maastricht MultiModal Molecular Imaging Institute, Maastricht University - The Netherland)
19. Metabolomics in human disease diagnosis (Jacopo Troisi – University of Salerno – Italy)
20. Fetal origin of adult disease: the metabolomics point of view (Vaisillios Fanos University of Cagliari – Italy)
21. Metabolomics as a tool for precision medicine (Bingbing Li – Shanghai University of Traditional Chinese Medicine, Shanghai – China)
22. Metabolomics in Public Health (Pierpaolo Cavallo – University of Salerno - Italy)

Details

No. of pages:
528
Language:
English
Copyright:
© Academic Press 2022
Published:
15th January 2022
Imprint:
Academic Press
Paperback ISBN:
9780323850629

About the Editor

Jacopo Troisi

Dr. Jacopo Troisi is a Research Scientist and COO at the European Biomedical Research Institute of Salerno (EBRIS), co-founded by the Harvard University and the Salerno Medical School. He is also co-founder and CEO at Theoreo srl, a spin-off company of the University of Salerno. Dr. Troisi research is related to metabolomics. In particular, he studies the metabolomic fingerprint of several human diseases to develop diagnostic tools. He has received several international patents for diagnostic tests based on metabolomic profiling. Dr. Troisi has published widely in such peer reviewed journals as Nature Microbiology, Frontiers in Immunology, Nutrients, BMC Microbiology, Nature Communications, and Scientific Reports.

Affiliations and Expertise

Research Scientist and COO, European Biomedical Research Institute of Salerno (EBRIS), Salerno, Italy

Ratings and Reviews