About this Research Topic
The objective of this Research Topic is to foster new methodologies that could overcome the above challenges. We welcome submissions to propose new effective and efficient methods for analyzing big data in imaging genomics, and yield promising biomedical discoveries to better understand the biological pathways and mechanisms from genetic determinants, molecular and cellular signatures, tissue and organ level biomarkers, and to phenotypical outcomes. Topics include but are not limited to:
• Genetic or epistatic analysis of imaging phenotypes
• Genomic or multi-omics analysis of imaging phenotypes
• Predictive modeling via integrative imaging genomics
• Statistical methods and causal reasoning in imaging genomics
• Machine learning and deep learning in imaging genomics
• Collaborative or federated learning in imaging genomics
• Big data analytics in imaging genomics
• Biomarker discovery in imaging genomics
• Systems biology in imaging genomics
• Translational imaging genomics
• Precision medicine in imaging genomics
• Clinical applications in imaging genomics
Keywords: imaging genomics, radiogenomics, medical image computing, bioinformatics, machine learning
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.