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- Computational Epigenetics and Disease
2. Computational Methods for Epigenomics Analysis
3. Statistical Approaches for Epigenetic Data Analysis
4. Bioinformatics Methodology Development for the Whole Genome Bisulfite Sequencing
5. Data Analysis of ChIP-Seq Experiments: Common Practice and Recent Developments
6. Computational Tools for MicroRNA Target Prediction
7. Integrative Analysis of Epigenomics Data
8. Differential DNA Methylation and Network Analysis in Schizophrenia
9. Epigenome-Wide DNA Methylation and Histone Modification Profiling in Alzheimer's Disease
10. Epigenomic Reprogramming in Cardiovascular Diseases
11. Bioinformatic and Biostatistic Methods for DNA Methylome Analysis of Obesity
12. Epigenomics of Diabetes Mellitus (Epigenetic Regulations in Diabetes Mellitus)
13. Epigenetic Profiling in Head and Neck Cancer
14. Epigenome-Wide DNA Methylation Profiles in Oral Cancer
15. Computational Epigenetics for Breast Cancer
16. Integrative Epigenomics of Prostate Cancer
17. Network Analysis of Epigenetics Data for Bladder Cancer
18. Epigenome-Wide Analysis of DNA Methylation in Colorectal Cancer
19. Integrative OMIC Analysis of Neuroblastoma
20. Computational Analysis of Epigenetic Modifications in Melanoma
21. DNA Methylome of Endometrial Cancer
22. Epigenetics and Epigenomics Analysis for Autoimmune Diseases
23. Computational Epigenetics in Lung Cancer
Computational Epigenetics and Diseases, written by leading scientists in this evolving field, provides a comprehensive and cutting-edge knowledge of computational epigenetics in human diseases. In particular, the major computational tools, databases, and strategies for computational epigenetics analysis, for example, DNA methylation, histone modifications, microRNA, noncoding RNA, and ceRNA, are summarized, in the context of human diseases.
This book discusses bioinformatics methods for epigenetic analysis specifically applied to human conditions such as aging, atherosclerosis, diabetes mellitus, schizophrenia, bipolar disorder, Alzheimer disease, Parkinson disease, liver and autoimmune disorders, and reproductive and respiratory diseases. Additionally, different organ cancers, such as breast, lung, and colon, are discussed.
This book is a valuable source for graduate students and researchers in genetics and bioinformatics, and several biomedical field members interested in applying computational epigenetics in their research.
- Provides a comprehensive and cutting-edge knowledge of computational epigenetics in human diseases
- Summarizes the major computational tools, databases, and strategies for computational epigenetics analysis, such as DNA methylation, histone modifications, microRNA, noncoding RNA, and ceRNA
- Covers the major milestones and future directions of computational epigenetics in various kinds of human diseases such as aging, atherosclerosis, diabetes, heart disease, neurological disorders, cancers, blood disorders, liver diseases, reproductive diseases, respiratory diseases, autoimmune diseases, human imprinting disorders, and infectious diseases
Graduate students on bioinformatics and genetics, bioinformaticians, healthcare professionals, pharmacologists, physicians
- No. of pages:
- © Academic Press 2019
- 11th February 2019
- Academic Press
- Hardcover ISBN:
- eBook ISBN:
Loo Keat Wei is Doctor of Philosophy on Human Genetics by Universiti Sains Maysia. Dr. Loo is a young scientist in Malaysia, who has showed a great interest and curiosity in the field of computational epigenetics. She has published several articles in this emerging field and has been awarded many prestigious international and national research grants such as Australia Endeavour Award, Ministry of Higher Education Fundamental Research Grant Scheme, Research Publication Schemes, Universiti Tunku Abdul Rahman Research Funds, etc., successfully securing more than USD $200,000 funds in the last three years. She is the member of International Stroke Genetics Consortium, Reviewer and Editorial Board Member in multiple journals.
Assistant Professor, Department of Biological Science, Faculty of Science, Universiti Tunku Abdul Rahman, Malaysia