Traditional and Machine-Learning-Based Approaches for Annotation of Natural Products
A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Bioinformatics and Data Analysis".
Deadline for manuscript submissions: closed (31 May 2024) | Viewed by 325
Special Issue Editors
Interests: metabolomics; compound identification; cheminformatics
Interests: metabolite identification; metabolomics; proteomics
Special Issue Information
Dear Colleagues,
We are pleased to announce a Special Issue of the journal Metabolites, dedicated to “Traditional and Machine-Learning-Based Approaches for Annotation of Natural Products". This Issue aims to bring together novel research and advancements in the interdisciplinary field of metabolomics and cheminformatics, with a particular emphasis on mass-spectrometry-based bioactive compound identification.
We welcome manuscripts that present innovative methodologies, algorithms, and software tools that leverage cheminformatics to annotate and identify natural products and their metabolites as well as any manual/heuristic approaches. We are interested in research that explores the use of mass spectrometry for comparing and interpreting complex spectra and for identifying novel bioactive compounds.
We also encourage submissions that delve into the discovery and identification of bioactive compounds, including the development and application of computational tools and databases. Contributions may encompass a broad range of topics, from the utilization of machine learning and artificial intelligence in compound identification to the integration of cheminformatics and metabolomics data for the discovery of naturally derived bioactive compounds.
This Special Issue aims to provide an international platform for researchers to share the latest developments and challenges in the rapidly evolving field of cheminformatics and metabolomics. We look forward to your contributions to this exciting area of research.
Dr. Ivana Blaženović
Dr. Yuanyue Li
Dr. Dejan C. Nikolić
Guest Editors
Manuscript Submission Information
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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 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
- machine learning
- bioactive compounds
- metabolomics
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