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.

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