Special Issue "Challenging Biochemical Complexities by NMR"
Deadline for manuscript submissions: closed (31 August 2016).
Nuclear Magnetic Resonance (NMR) has strong advantages for the structure determination of metabolites, therefore, it has been used significantly in chemical analysis, namely with purified natural products. However, NMR has also great potential to analyze un-purified, biochemical mixtures, including in situ/in vivo sample systems. With this feature, NMR has also been contributed to metabolomics/metabonomics studies, also applied for macromolecular mixtures, including foods and biomass. Recent technical advances for signal separation of crowded regions, using high-field magnets, allow more accurate analysis of biochemical mixtures. Furthermore, the hardware development of low-field magnets also has potential to open a new avenue for on-site analysis of agricultural/industrial products, as well as human samples, without performing laboratory sample preparation.
This Special Issue of Metabolites will be focused on cutting-edge technologies for sampling, measurements, and analysis, both from a fundamental, as well as an applied point of view. The topics that shall be covered by this Special Issue include recent developments of hardware or related apparatus including benchtop NMR. The sample preparation method is also a key feature to be covered, as well as efficient extraction, concentration of dilute sample system, stable isotope labeling, and in situ/in vivo measurements. Therefore, sample systems can also be widely covered, not only laboratory-made biochemical extracts, but also in agriculture, forestry, and fishery products, such as foods, woods, and their process monitoring, environmental complexity, such as plants, animals, unculturable microbiota, as well as geochemical samples, human related samples, biochemically degradable system such as historical heritage. The inter-convertibility of NMR data among different institutions is also a distinct advantage for the NMR-based approach, therefore, database construction of obtained large amounts of biological data and its computation, as well as chemoinformatics, are also important issues. Manuscripts dealing with other challenging issues in the field of biochemical mixture analysis are also highly welcome.
Dr. Jun Kikuchi
Relevant Special Issue can be found here: https://www.mdpi.com/journal/metabolites/special_issues/NMR.
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 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 2000 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.
- agriculture, forestry and fishery
- large amounts of biological data and its computation
- diffusion and mobility-based separation
- environmental complexity
- historical heritage
- human health
- industrial process
- inorganic mixtures
- isotope labeling
- macromolecular mixtures
- metabolite mixtures
- sampling technique
- signal deconvolution