The Spatial Metabolome Revealed: AI and Deep Learning in Tissue-Level Molecular Mapping
A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Bioinformatics and Data Analysis".
Deadline for manuscript submissions: 31 October 2026 | Viewed by 211
Special Issue Editors
Interests: artificial intelligence; deep learning; computational biology; disease pre-diction; metabolomics; biomarker discovery; explainable AI; gene regu-lation; multi-omics integration; precision medicine; therapeutic target identification
Interests: modeling; inflammation; system identification; proteomics; prediction; biotechnology; myocardial infarction; network; robotics; bioinformatics
Special Issue Information
Dear Colleagues,
The rapid convergence of artificial intelligence (AI), deep learning (DL), and spatial omics technologies is revolutionizing biomedical research. This Special Issue will focus on recent advances in AI- and DL-based methodologies for integrating and interpreting spatial transcriptomics and metabolomics data. These technologies enable unprecedented resolution in mapping gene expression and metabolic activity within the spatial context of tissues, providing critical insights into disease mechanisms, metabolic dysregulation, and therapeutic response.
The overarching goal of this Special Issue is to bring together computational and experimental advances that address the challenges of high-dimensional, spatially resolved data analysis. We particularly encourage contributions that present interpretable and biologically explainable AI/DL frameworks that go beyond prediction to reveal a mechanistic understanding of the metabolic pathways, cell–cell communication, and regulatory networks that drive tissue organization and disease progression.
The scope of this Special Issue spans novel computational models, data integration strategies, and translational applications across diverse disease areas, including cancer, metabolic, infectious, and immune-related disorders. We invite studies that develop and validate tools for mapping spatial metabolic niches, identifying biomarkers, modeling metabolic fluxes, and discovering therapeutic targets.
Topics of interest for this Special Issue include, but are not limited to, the following:
- Development of AI/DL tools for integrated spatial transcriptomic and metabolomic analyses.
- Methods to map cellular heterogeneity, spatial metabolic niches, and metabolite-driven signaling networks.
- Predictive modeling of metabolic pathway dysregulation, gene–metabolite interactions, and disease trajectories.
- AI-driven discovery of spatial biomarkers, metabolic vulnerabilities, and therapeutic targets.
- Translational applications of spatial AI in cancer, metabolic, infectious, and immune-related diseases.
- Advances in model interpretability, biological validation, and clinical translation.
By highlighting these innovations, this Special Issue aims to advance the integration of spatial transcriptomic and metabolomic data into actionable biomedical insights. Ultimately, we seek to foster collaboration among computational biologists, systems scientists, and clinicians to push the boundaries of precision medicine through a deeper understanding of spatial metabolism and molecular organization in health and disease.
Dr. Mario Flores
Dr. Yufang Jin
Guest Editors
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-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
- artificial intelligence
- deep learning
- spatial transcriptomics
- spatial metabolomics
- computational biology
- biomarker discovery
- metabolic pathways
- precision medicine
- multi-omics integration
- disease modeling
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