Bioinformatics for Mass Spectrometry-Based Metabolomics View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2011-01-29

AUTHORS

David P. Enot , Bernd Haas , Klaus M. Weinberger

ABSTRACT

The broad view of the state of biological systems cannot be complete without the added value of integrating proteomic and genomic data with metabolite measurement. By definition, metabolomics aims at quantifying not less than the totality of small molecules present in a biofluid, tissue, organism, or any material beyond living systems. To cope with the complexity of the task, mass spectrometry (MS) is the most promising analytical environment to fulfill increasing appetite for more accurate and larger view of the metabolome while providing sufficient data generation throughput. Bioinformatics and associated disciplines naturally play a central role in bridging the gap between fast evolving technology and domain experts. Here, we describe the strategies to translate crude MS information into features characteristics of metabolites, and resources available to guide scientists along the metabolomics pipeline. A particular emphasis is put on pragmatic solutions to interpret the outcome of metabolomics experiments at the level of signal processing, statistical treatment, and biochemical understanding. More... »

PAGES

351-375

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-61779-027-0_16

DOI

http://dx.doi.org/10.1007/978-1-61779-027-0_16

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1026693191

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/21370092


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