Integrative Omics in Parkinson's Disease provides a comprehensive understanding of the current literature on high-throughput technologies relating to discoveries for Parkinson's disease etiology. This emerging field uses large omics datasets to investigate the etiology of Parkinson's disease and other forms of parkinsonism. The book traces the evolution of omics technologies from the discovery of monogenic Parkinson's disease forms. Chapters delve into genomics, transcriptomics, epigenomics, artificial intelligence, and gene-environment interactions. Furthermore, it examines the potential therapeutic applications of these advancements and provides insights into the future of omics research in Parkinson's disease.
- Reviews evolution of omics technologies from the first identification of monogenic forms of Parkinson's disease
- Outlines machine learning algorithm application to Parkinson's disease datasets
- Reviews big datasets on gene-environment interactions, genomics, epigenetics, and transcriptomics
- Identifies how the microbiome influences Parkinson's disease in mouse models and patients
- Provides outlook for therapies with induced-pluripotent stem cell models
Sprache
Verlagsort
Verlagsgruppe
Elsevier Science & Techn.
Dateigröße
ISBN-13
978-0-443-13551-4 (9780443135514)
Schweitzer Klassifikation
1. Introduction: evolution of omics2. Monogenic and Complex genetics PD3. Genetic risk scores4. Mendelian Randomization5. Methods to investigate somatic structural variants in synucleinopathies6. Mitochondrial genetics7. Epigenetics in PD genes8. The microbiome9. Genetic modifiers in reduced penetrance: X-linked dystonia10. Long-read transcriptomics in neurodegeneration11. Gene-environment interactions and behaviour12. Introduction to prediction modeling using machine learning and omics data13. IPSCs and OMICs merging
