In the field of neuroscience, we are witnessing a transformative era driven by the exponential increase in data generation and advanced data analysis technologies. The integration of big data mining in medical research has revolutionized the way we understand and address neurological disorders. These disorders are a leading cause of mortality and long-term disability globally, placing a heavy burden economically and socially. However, the availability and computational application of publicly accessible large-scale databases offer an unprecedented opportunity to address these challenges. Databases such as Surveillance, Epidemiology, and End Results (SEER), Medical Information Mart for Intensive Care (MIMIC), National Health and Nutrition Examination Survey (NHANES), UK Biobank, and Gene Expression Omnibus (GEO), provide pivotal resources for unveiling crucial insights through novel data mining approaches. Although progress has been made, limitations in the application and interpretation of these large-scale data sets persist, necessitating more comprehensive explorations in this domain.
This Research Topic aims to capitalize on big data capabilities to unravel latent patterns in neurological disorder datasets, ultimately enhancing our grasp of these conditions. By harnessing the vast potential of big data mining, the research intends to drive forward neurological studies, support evidence-based clinical decisions, refine therapeutic interventions, and improve patient outcomes. Addressing these aims involves answering several key questions: What new patterns can be identified in existing datasets? How can big data inform clinical strategies for neurological conditions? And what methodologies can be employed to validate findings encountered in publicly available data?
To gather further insights into the expansive possibilities of big data mining in neuroscience research, submissions are invited that focus on various themes within this scope. These include, but are not limited to, the following:
• Global trends in the incidence and prevalence of neurological disorders
• The global burden of neurological diseases
• Risk factor analysis and predictive model development for neurological disorders
• Identification of pathogenic genes and mechanisms underlying neurological disorders
• Single-cell atlas and spatial transcriptomic map of neurological diseases
Researchers are encouraged to contribute findings from both publicly available and locally sourced datasets to ensure robust and comprehensive conclusions across diverse population groups.
Keywords: big data mining, neurological disorders, global burden, risk factors, prediction model, pathogenic genes, data analysis techniques, single-cell atlas, spatial transcriptomic map
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.
