Special Issue "Big Data in Metabolomics"

A special issue of Metabolites (ISSN 2218-1989).

Deadline for manuscript submissions: closed (30 September 2017)

Special Issue Editors

Guest Editor
Prof. Dr. Jan Baumbach

TUM School of Life Sciences Weihenstephan, Technical University of Munich, Germany​
Website 1 | Website 2 | E-Mail
Interests: metabolomics; biomarker discovery; disease classification; ion mobility spectrometry
Guest Editor
Dr. Richard Röttger

Practical Computer Science and Bioinformatics, Department of Mathematics and Computer Science (IMADA), University of Southern Denmark, Compusvej 50, DK-5230 Odense M, Denmark
Website | E-Mail
Interests: machine learning; classification; clustering; systems biology; biological network analysis

Special Issue Information

Dear Colleagues,

Metabolomics is an important branch of the so-called "OMICS" field, investigating small molecules and compounds, the metabolites from a system biological perspective. It serves multiple purposes, from early disease detection, patient separation, treatment optimization to a generally better understanding of the metabolic systems in a cell, tissue or organism. Due to the proven usefulness and success combined with more and more advanced wet-lab techniques, metabolomics is producing an increasing amount of high-quality data in an ever increasing pace. This fact can be summarized under the umbrella of "Big Data" in terms of velocity (the pace data is generated), volume (the sheer amount of data) and variety (the multitude of different data sources). In addition to the huge opportunities arising from having these rich data sources at hand they pose hard challenges at the same time. This requires sophisticated computational methods for data management, analysis and the meaningful integration of a multitude of different and heterogeneous data sources. The recent advances have led to the intention to initiate this special issue of Metabolites with an emphasis of the challenges and solutions arising in the age of Big Data in metabolomics research.

Dr. Jan Baumbach
Dr. Richard Röttger
Guest Editors

Relevant special issues can be found here: http://www.mdpi.com/journal/metabolites/special_issues/data_processing.

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 850 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (1 paper)

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Review

Open AccessReview Biomarker Research in Parkinson’s Disease Using Metabolite Profiling
Metabolites 2017, 7(3), 42; https://doi.org/10.3390/metabo7030042
Received: 26 June 2017 / Revised: 8 August 2017 / Accepted: 9 August 2017 / Published: 11 August 2017
Cited by 4 | PDF Full-text (729 KB) | HTML Full-text | XML Full-text
Abstract
Biomarker research in Parkinson’s disease (PD) has long been dominated by measuring dopamine metabolites or alpha-synuclein in cerebrospinal fluid. However, these markers do not allow early detection, precise prognosis or monitoring of disease progression. Moreover, PD is now considered a multifactorial disease, which
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Biomarker research in Parkinson’s disease (PD) has long been dominated by measuring dopamine metabolites or alpha-synuclein in cerebrospinal fluid. However, these markers do not allow early detection, precise prognosis or monitoring of disease progression. Moreover, PD is now considered a multifactorial disease, which requires a more precise diagnosis and personalized medication to obtain optimal outcome. In recent years, advanced metabolite profiling of body fluids like serum/plasma, CSF or urine, known as “metabolomics”, has become a powerful and promising tool to identify novel biomarkers or “metabolic fingerprints” characteristic for PD at various stages of disease. In this review, we discuss metabolite profiling in clinical and experimental PD. We briefly review the use of different analytical platforms and methodologies and discuss the obtained results, the involved metabolic pathways, the potential as a biomarker and the significance of understanding the pathophysiology of PD. Many of the studies report alterations in alanine, branched-chain amino acids and fatty acid metabolism, all pointing to mitochondrial dysfunction in PD. Aromatic amino acids (phenylalanine, tyrosine, tryptophan) and purine metabolism (uric acid) are also altered in most metabolite profiling studies in PD. Full article
(This article belongs to the Special Issue Big Data in Metabolomics)
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