New Development Trends of Mass Spectrometry-Driven Metabolomics
A Special Issue of Metabolites (ISSN 2218-1989) belonging to the section "Advances in Metabolomics".
Deadline for manuscript submissions: 31 March 2027 | Viewed by 117
Editor
Special Issue Information
Dear Colleagues,
Mass spectrometry (MS)-based metabolomics has become one of the most transformative technologies in modern life sciences, enabling comprehensive characterization of metabolites that reflect dynamic biological processes and disease states. Over the past decade, rapid advances in MS instrumentation, analytical methodologies, computational tools, and systems biology have substantially expanded the depth, sensitivity, and translational potential of metabolomics. Emerging technologies such as ion mobility spectrometry, imaging and spatial metabolomics, ambient ionization, single-cell metabolomics, and portable miniaturized MS platforms are opening unprecedented opportunities for real-time molecular phenotyping and precision diagnostics.
At the same time, the integration of metabolomics with other omics disciplines, together with advances in AI, machine learning, and network-based data analysis, is transforming our ability to extract biologically meaningful insights from increasingly complex datasets. These developments are driving new discoveries across a broad range of fields, including cardiovascular and metabolic diseases, cancer, neuroscience, psychiatry, microbiome research, nutrition, environmental health, pharmaceutical sciences, and precision medicine.
This Special Issue aims to provide a timely forum for highlighting the latest technological innovations, methodological developments, and translational applications that are shaping the future of MS-based metabolomics. We welcome contributions covering targeted and untargeted metabolomics, lipidomics, metabolite imaging, bioinformatics, data integration, standardization, quality assurance, and emerging analytical platforms. Particular emphasis will be placed on studies that bridge technological advances with biological, clinical, environmental, or industrial applications.
By bringing together researchers from diverse disciplines, this Special Issue seeks to showcase current breakthroughs, address existing challenges, and provide new directions that will advance the next generation of metabolomics research and its impact on human health and society.
Dr. Xiaosuo Wang
Guest Editor
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 submissions that pass pre-check are 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 250 words) can be sent to the Editorial Office for assessment.
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-anonymized 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 monthly 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 2700 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.
Keywords
- mass spectrometry
- metabolomics
- lipidomics
- spatial metabolomics
- imaging mass spectrometry
- miniature mass spectrometry
- multi-omics integration
- biomarker discovery
- precision medicine
- artificial intelligence
- systems biology
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