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Integrative Omics in Parkinson's Disease
- 1st Edition - November 21, 2024
- Editor: Joanne Trinh
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 1 3 5 5 0 - 7
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 3 5 5 1 - 4
Integrative Omics in Parkinson’s Disease provides a comprehensive understanding of the current literature on high-throughput technologies relating to discoveries for Parkinson's… Read more
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Request a sales quoteIntegrative 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
Researchers, Clinicians, and students in Parkinson’s disease
1. Introduction: evolution of omics
2. Monogenic and Complex genetics PD
3. Genetic risk scores
4. Mendelian Randomization
5. Methods to investigate somatic structural variants in synucleinopathies
6. Mitochondrial genetics
7. Epigenetics in PD genes
8. The microbiome
9. Genetic modifiers in reduced penetrance: X-linked dystonia
10. Long-read transcriptomics in neurodegeneration
11. Gene-environment interactions and behaviour
12. Introduction to prediction modeling using machine learning and omics data
13. IPSCs and OMICs merging
2. Monogenic and Complex genetics PD
3. Genetic risk scores
4. Mendelian Randomization
5. Methods to investigate somatic structural variants in synucleinopathies
6. Mitochondrial genetics
7. Epigenetics in PD genes
8. The microbiome
9. Genetic modifiers in reduced penetrance: X-linked dystonia
10. Long-read transcriptomics in neurodegeneration
11. Gene-environment interactions and behaviour
12. Introduction to prediction modeling using machine learning and omics data
13. IPSCs and OMICs merging
- No. of pages: 300
- Language: English
- Edition: 1
- Published: November 21, 2024
- Imprint: Academic Press
- Paperback ISBN: 9780443135507
- eBook ISBN: 9780443135514
JT
Joanne Trinh
Joanne Trinh, Ph.D., is a Heisenberg professor at the Institute of Neurogenetics, University of Lübeck. Dr. Joanne Trinh received her doctorate in medical genetics at the University of British Columbia. She subsequently joined the Institute of Neurogenetics in Lübeck, where she obtained a faculty position. She is now head of the “Integrative Omics in Parkinson’s Disease” research group, which investigates the role of mosaic variants, nuclear and mitochondrial genome sequences, and lifestyle and environmental factors in parkinsonism. She is on the editorial board of Annals of Neurology and an associate editor of Frontiers in Neurology. Her research group in Lübeck will continue to use big-data approaches to elucidate the causes of neurological disease.
Affiliations and expertise
Institute of Neurogenetics, University of Lübeck, Germany