AI and Machine Learning in Molecular Biomarker Discovery and Mechanisms of Neurodegenerative Disorders

Dear Colleagues,

The transformative potential of machine learning (ML) and artificial intelligence (AI) is reshaping molecular research in neurodegenerative disorders, such as Alzheimer’s disease (AD), Parkinson’s disease (PD), dementia, and mild cognitive impairment (MCI). This Special Issue seeks to highlight ML/AI applications in the analysis of molecular biomarkers, genetic and multi-omics data (genomics, proteomics, metabolomics), and molecular mechanisms underlying neurodegeneration. We invite original research, reviews, and computational studies exploring AI-driven approaches for integrating molecular datasets, identifying novel molecular targets, and elucidating pathways involved in disease onset and progression. Topics include, but are not limited to, machine learning methods for biomarker discovery at the molecular level, prediction of disease risk and progression using molecular data, AI-facilitated classification of molecular subtypes, and integrative omics strategies. Submissions should emphasize translational applications that connect molecular findings to clinical insights, such as improving early diagnosis or identifying potential therapeutic targets. By fostering interdisciplinary collaboration, this issue aims to advance AI/ML-driven molecular discoveries, ultimately enhancing our understanding and treatment of neurodegenerative disorders.

Dr. Seyed Ehsan Saffari
Guest Editor

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