Integrating Bioinformatics and AI to Unravel Multi-Organ Dynamics and Therapeutic Avenues in Renal Diseases

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About this Research Topic

This Research Topic is still accepting articles.

Background

Renal diseases such as chronic kidney disease, acute kidney injury, and renal cancers pose critical challenges on a global scale. These illnesses often extend beyond the kidneys, involving complex interactions between multiple organs like the heart, liver, and brain. Despite improvements in clinical treatments, significant gaps remain in understanding these multi-organ connections and developing targeted therapies. Recent advances in bioinformatics and artificial intelligence provide innovative avenues to tackle these challenges. By harnessing multi-omics data, and leveraging spatial-temporal modeling alongside clinical informatics, these tools aid in unveiling the molecular cross-talk and dynamic microenvironmental changes driving disease progression. In this Research Topic, we call for pioneering contributions at the crossroads of computational biology, immunology, and nephrology to enhance our comprehension of renal diseases and their systemic effects.

This Research Topic aims to integrate computational advancements with biological research to illuminate the dynamics of multi-organ interactions in renal disease. Key objectives include understanding the underlying mechanisms of organ crosstalk, identifying potential biomarkers, and developing innovative therapeutic strategies. We seek to address unanswered questions and test hypotheses related to systemic manifestations of renal diseases, employing advanced AI techniques and comprehensive bioinformatics approaches to foster new knowledge in this domain.

To gather further insights into this complex field, we welcome articles addressing, but not limited to, the following themes:

o Mechanisms of renal-cardiac, renal-cerebral, and renal-hepatic interactions explored through single-cell omics, cytokine networks, or AI-driven modeling.

o Immune, stromal, and epithelial dynamics contributing to renal diseases and their systemic impacts, including insights into the gut-kidney axis.

o AI-powered discovery of pathway transitions and epigenetic drivers in disease processes like AKI-to-CKD and CKD-related cognitive decline.

o Innovative therapeutic approaches such as network pharmacology, drug repurposing, and CRISPR-based interventions for multi-organ complications.

o Technological advancements including novel algorithms and tools for digital pathology, prognostic modeling, and 3D visualizations.

o Platforms for visualizing cross-organ signaling and immune cell trafficking in renal-systemic diseases.

Submission Guidelines: We invite original research, reviews, methods, and perspectives with a focus on computational rigor, clinical relevance, and biological insights. Emphasizing studies that combine AI predictions and bioinformatics analyses with experimental validation, including models and multi-omics data, are particularly encouraged.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

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  • Case Report
  • Clinical Trial
  • Community Case Study
  • Data Report
  • Editorial
  • FAIR² Data
  • FAIR² DATA Direct Submission
  • General Commentary

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Keywords: renal disease, multi-organ crosstalk, bioinformatics, artificial intelligence, multi-omics, biomarkers, therapeutic strategies, immune dynamics, computational modeling, systemic manifestations

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Topic editors

Manuscripts can be submitted to this Research Topic via the main journal or any other participating journal.

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