Advances and Applications of Metabolomics in Human Diseases
A special issue of Diseases (ISSN 2079-9721).
Deadline for manuscript submissions: closed (31 July 2015) | Viewed by 19978
Special Issue Editor
Special Issue Information
Dear Colleagues,
Metabolomics, as an emerging field of ‘omics’ technologies, is defined as comparative analysis of the metabolites present in a biological system or a specified physiological state. It aims to characterize and identify metabolites – the end products of cellular metabolism. As an interdisciplinary field of science, metabolomics combines analytical chemistry, bioinformatics, statistics, and biochemistry. When applied to human disease studies, metabolomics also includes aspects of patho-biochemistry, systems biology, and molecular diagnostics.
This Special Issue will focus on the advances and applications of metabolomics in human diseases. Metabolomics has been in the focus for the past few years as diagnostic and screening tool for disease recognition. There are already plenty of test cases demonstrating the validity of such approaches. However, there are also severe practical and theoretical constraints known if applying metabolic profiling as universal tool for improved understanding and diagnostics of disease patterns. Potential topics related to this special issue include, but not limited to:
- Analytical methods development in metabolomics;
- Bioinformatics tools for data processing and pathway analysis;
- Method development for metabolite identification;
- Discovery of new markers for human diseases;
- Methods for ‘omics’ data integration for human disease study;
- Integration of metabolomics and clinical data for diagnosis or therapeutic applications;
I highly encourage authors to submit original papers and reviews for this Special Issue.
Dr. Liang Zhao
Guest Editor
Manuscript Submission Information
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Keywords
- metabolomics
- metabolic profiling
- untargeted approach
- targeted approach
- mass spectrometry
- biomarker
- diagnostics
- plasma
- serum
- urine
- mammalian cells
- multivariate statistics
- pathway analysis
- omics technology
- systems biology
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