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.
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Table of Contents
1. 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
