Computational Epigenetics and Diseases

 
 
Elsevier (Verlag)
  • 1. Auflage
  • |
  • erschienen am 6. Februar 2019
  • |
  • 450 Seiten
 
E-Book | ePUB mit Adobe-DRM | Systemvoraussetzungen
E-Book | PDF mit Adobe-DRM | Systemvoraussetzungen
978-0-12-814514-2 (ISBN)
 

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
  • Englisch
  • San Diego
  • |
  • USA
  • 12,17 MB
978-0-12-814514-2 (9780128145142)
weitere Ausgaben werden ermittelt
  • Front Cover
  • Computational Epigenetics and Diseases
  • Translational Epigenetics Series
  • Computational Epigenetics and Diseases
  • Copyright
  • Contents
  • Contributors
  • 1 - COMPUTATIONAL EPIGENETICS AND DISEASE
  • INTRODUCTION
  • COMPUTATIONAL APPROACHES IN DNA METHYLATION
  • COMPUTATIONAL APPROACHES IN HISTONE MODIFICATIONS
  • COMPUTATIONAL APPROACHES IN MIRNAS
  • COMPUTATIONAL EPIGENETICS IN METABOLIC AND CARDIAC DISORDERS
  • COMPUTATIONAL EPIGENETICS IN NEUROLOGICAL DISORDERS
  • COMPUTATIONAL EPIGENETICS AND CANCER
  • CONCLUSIONS
  • ACKNOWLEDGMENT
  • REFERENCES
  • 2 - COMPUTATIONAL METHODS FOR EPIGENOMIC ANALYSIS
  • INTRODUCTION
  • UNBIASED DETECTION OF CHIP-ENRICHMENT
  • SEGMENTATION OF THE EPIGENOME INTO CHROMATIN STATES
  • THE DIFFERENTIAL EPIGENOME
  • REFERENCES
  • 3 - STATISTICAL APPROACHES FOR EPIGENETIC DATA ANALYSIS
  • INTRODUCTION
  • STATISTICAL MODELING
  • STATISTICAL METHODOLOGY
  • FORMULATION OF MULTIPLE TEST PROBLEMS
  • TEST STATISTICS AND THEIR LIMITING NULL DISTRIBUTIONS
  • MULTIPLE TEST PROCEDURES: CLOSURE PRINCIPLE
  • FINITE SAMPLE MODIFICATION: STUDENTIZED PERMUTATION APPROACH
  • REAL DATA ANALYSIS
  • DISCUSSION
  • ACKNOWLEDGMENTS
  • REFERENCES
  • 4 - BIOINFORMATICS METHODOLOGY DEVELOPMENT FOR THE WHOLE GENOME BISULFITE SEQUENCING
  • INTRODUCTION
  • RESULTS
  • BETA-BINOMIAL HIERARCHICAL MODEL FOR BOTH SAMPLING AND BIOLOGICAL VARIATIONS
  • CREDIBLE METHYLATION DIFFERENCE (CDIF) IS A SINGLE METRIC FOR BOTH STATISTICAL AND BIOLOGICAL SIGNIFICANCE OF DIFFERENTIAL ...
  • FUNCTIONS AND PERFORMANCE OF THE MOABS PIPELINE
  • SIMULATED BS-SEQ DATA REVEAL THE SUPERIOR PERFORMANCE OF MOABS
  • MOABS IMPROVES THE DETECTION OF ALLELE-SPECIFIC DNA METHYLATION
  • MOABS RELIABLY REVEALS DIFFERENTIAL METHYLATION UNDERLYING TFBSS
  • MOABS DETECTS DIFFERENTIAL 5HMC IN ES CELLS USING RRBS AND OXBS-SEQ
  • DISCUSSION
  • METHODS
  • DISTRIBUTION FOR DIFFERENCE OF TWO BINOMIAL PROPORTIONS
  • DISTRIBUTION FOR DIFFERENCE OF DIFFERENCE
  • DISTRIBUTION FOR MEASUREMENTS WITH REPLICATES
  • ACKNOWLEDGMENTS
  • REFERENCES
  • SUPPLEMENTARY METHODS
  • METHYLATION RATIO OF ONE LOCUS FOLLOWS A BETA DISTRIBUTION
  • CI FOR SINGLE BINOMIAL PROPORTION
  • CI FOR DIFFERENCE OF TWO BINOMIAL PROPORTIONS IN DETAIL
  • IDENTIFICATION OF DMCS FOR TWO OR MORE SAMPLES
  • IDENTIFICATION OF DMRS FOR TWO SAMPLES BY SIMPLY GROUPING DMCS
  • IDENTIFICATION OF DMRS FOR TWO SAMPLES BY HIDDEN MARKOV MODEL
  • IDENTIFICATION HYPOMETHYLATED REGIONS FROM ONE SAMPLE
  • SUPPLEMENTARY REFERENCES
  • 5 - DATA ANALYSIS OF CHIP-SEQ EXPERIMENTS: COMMON PRACTICE AND RECENT DEVELOPMENTS
  • THE DESIGN OF CHIP-SEQ
  • THE QUALITY OF CHIP-SEQ DATA
  • MAPPING CHIP-SEQ READS
  • PEAK CALLING
  • DIFFERENTIAL ENRICHMENT DETECTION
  • ALL-IN-ONE DATA ANALYSIS PIPELINES FOR CHIP-SEQ
  • BEYOND THE STANDARD PIPELINE: ALLELIC-IMBALANCE DETECTION FROM CHIP-SEQ
  • SUMMARY
  • REFERENCES
  • 6 - COMPUTATIONAL TOOLS FOR MICRORNA TARGET PREDICTION
  • INTRODUCTION
  • PRINCIPLES OF MICRORNA TARGET PREDICTION
  • SEED SEQUENCE COMPLEMENTARITY
  • FREE ENERGY
  • G-U WOBBLE
  • EVOLUTIONARY CONSERVATION STATUS
  • 3´ UTR COMPENSATORY BINDING
  • TARGET-SITE ACCESSIBILITY
  • TARGET-SITE ABUNDANCE
  • LOCAL AU FLANKING CONTENT
  • MACHINE LEARNING
  • PATTERN-BASED APPROACH
  • MICRORNA TARGET PREDICTION TOOLS
  • CONCLUSION AND FUTURE DIRECTION
  • REFERENCES
  • FURTHER READING
  • 7 - INTEGRATIVE ANALYSIS OF EPIGENOMICS DATA
  • INTRODUCTION
  • QUALITY CONTROL AND DATA PREPROCESSING
  • RELATIONSHIP BETWEEN HISTONE MODIFICATION PATTERN, TRANSCRIPTION FACTOR BINDING, AND MRNA EXPRESSION LEVEL
  • REGRESSION ANALYSIS
  • MIXTURE MODEL
  • IDENTIFICATION OF FUNCTIONAL REGULATORY REGIONS
  • ASSOCIATION BETWEEN MULTIPLE TRANSCRIPTION FACTORS USING SELF-ORGANIZING MAP (SOM)
  • PREDICTION OF CHROMATIN AND TRANSCRIPTION BINDING SITES DIRECTLY FROM DNA SEQUENCES USING DEEP LEARNING
  • DISCUSSION
  • ACKNOWLEDGMENTS
  • REFERENCES
  • 8 - DIFFERENTIAL DNA METHYLATION AND NETWORK ANALYSIS IN SCHIZOPHRENIA
  • INTRODUCTION
  • METHODOLOGY FOR DNA METHYLATION
  • METHYLATION SCHIZOPHRENIA NETWORK
  • NOVEL PREDICTION APPLICATIONS
  • CANDIDATE GENES IN SCHIZOPHRENIA
  • SDMGS AND DISEASE MECHANISM OF SCHIZOPHRENIA
  • CORRESPONDING PATHWAYS AND SCHIZOPHRENIA
  • SCHIZOPHRENIA AND EPIGENETIC REVIEW
  • FINDINGS HIGHLIGHT THE SIGNIFICANCE OF ANTIPSYCHOTIC DRUGS ON DNA METHYLATION IN SCHIZOPHRENIA PATIENTS
  • REFERENCES
  • 9 - EPIGENOME-WIDE DNA METHYLATION AND HISTONE MODIFICATION OF ALZHEIMER'S DISEASE
  • BACKGROUND
  • EPIGENETICS ASSOCIATION WITH THE NERVOUS SYSTEM
  • EPIGENETIC MECHANISMS IN AD
  • EPIGENETIC CHANGES IN AD
  • EPIGENETIC MODIFICATIONS
  • DNA METHYLATION
  • HYPOMETHYLATION IN AD
  • HYDROXYMETHYLATION IN AD
  • GENE-WISE DNA METHYLATION CHANGES IN AD
  • GENOME-WIDE DNA METHYLATION ALTERATIONS IN AD
  • DNA REPAIR AND METHYLATION IN AD
  • HISTONE MODIFICATIONS
  • HISTONE ACETYLATION CHANGES IN AD
  • GENE-WISE HISTONE ALTERATIONS IN AD
  • EPIGENOMICS
  • MOLECULAR MECHANISMS LINKING GENOMIC RISK FACTORS TO AD
  • POLYMORPHISMS AND AD
  • SYSTEMS LEVEL MODULES FOR AD
  • FUTURE DIRECTIONS
  • REFERENCES
  • FURTHER READING
  • 10 - EPIGENOMIC REPROGRAMMING IN CARDIOVASCULAR DISEASE
  • INTRODUCTION
  • DECIPHER HISTONE CODES OF CM TRANSCRIPTION
  • IDENTIFY CHROMATIN MODIFICATION LANDSCAPES AND DYNAMICS DURING HEART DEVELOPMENT
  • DYNAMICS OF REGULATORY CIS-ELEMENTS IN HEART DISEASE
  • DNA METHYLATION DURING HEART DEVELOPMENT AND IN DISEASE
  • DNA METHYLATION IS ORCHESTRATED IN NORMAL HEART
  • DNA METHYLATION IS POTENTIAL THERAPEUTIC TARGET IN HEART DISEASE
  • DNA HYDROXYMETHYLATION REGULATES GENE EXPRESSION IN CARDIAC DEVELOPMENT AND HYPERTROPHY
  • CHROMATIN CONFORMATION IN CARDIOMYOCYTES
  • RAPID CHROMATIN SWITCH DURING SOMATIC REPROGRAMMING
  • CONCLUSION
  • REFERENCES
  • 11 - BIOINFORMATIC AND BIOSTATISTIC METHODS FOR DNA METHYLOME ANALYSIS OF OBESITY
  • WHICH DNA METHYLATION ASSESSMENT TECHNIQUE SHOULD I USE?
  • WHICH SOFTWARE AND DATA SETS SHOULD I USE TO ANALYZE DNA METHYLATION DATA IN THE CONTEXT OF OBESITY?
  • HOW DO I ANNOTATE MY DMRS TO SPECIFIC GENES?
  • WHAT DOES A DIFFERENCE OF 5% IN METHYLATION MEAN?
  • HOW DO I KNOW WHETHER MY DMRS ARE A CAUSE OR A CONSEQUENCE OF OBESITY?
  • HOW CAN I BE SURE THAT MY DMRS ARE NOT DUE TO DIFFERENCES IN CELL TYPE PROPORTIONS?
  • REFERENCES
  • 12 - EPIGENOMICS OF DIABETES MELLITUS
  • BASICS OF EPIGENETICS
  • EPIGENETIC REGULATION IN TYPE 2 DIABETES MELLITUS
  • EPIGENETICS IN VASCULAR COMPLICATIONS OF TYPE 2 DIABETES MELLITUS
  • EPIGENETICS AND CANCER DEVELOPMENT IN TYPE 2 DIABETES MELLITUS
  • ROLE OF MICRORNAS (MIRNAS) IN TYPE 2 DIABETES MELLITUS
  • FUTURE PERSPECTIVES AND EPIGENETIC DRUGS
  • CONCLUSION
  • REFERENCES
  • 13 - EPIGENETIC PROFILING IN HEAD AND NECK CANCER
  • INTRODUCTION
  • EPIGENETIC ALTERATIONS IN CANCER
  • DNA METHYLATION PROFILING IN HEAD AND NECK CANCER
  • TECHNIQUES AVAILABLE FOR EPIGENETIC PROFILING OF HNC
  • METHYLATION SPECIFIC PCR
  • COMBINED BISULFITE RESTRICTION ANALYSIS ASSAY
  • BISULFITE SEQUENCING
  • PYROSEQUENCING
  • WHOLE GENOME BISULFITE SEQUENCING
  • ARRAY OR BEAD HYBRIDIZATION TECHNIQUES FOR EPIGENETIC PROFILING
  • ENRICHMENT-BASED METHODS
  • METHYLATED DNA IMMUNOPRECIPITATION
  • COMPUTATIONAL EPIGENETICS ANALYSIS
  • BIOINFORMATICS TOOLS FOR COMPUTATIONAL EPIGENOMICS
  • METHODS FOR ANALYZING AND INTERPRETING THE DNA METHYLATION DATA
  • Data Processing of Bisulfite-Sequencing Data
  • Data Processing of Bisulfite Microarray Data
  • Data Processing of Enrichment-Based Data
  • Data Visualization and Statistical Analysis
  • CONCLUSION AND FUTURE PERSPECTIVES
  • REFERENCES
  • 14 - EPIGENOME-WIDE DNA METHYLATION PROFILES IN ORAL CANCER
  • INTRODUCTION
  • EPIGENETIC REGULATION IN ORAL CANCER
  • NEED FOR COMPUTATIONAL TOOLS IN EPIGENETICS STUDY
  • AVAILABLE METHODS AND COMPUTATIONAL TOOLS FOR ORAL CANCER METHYLOMICS
  • TOOLS FOR METHYLOMICS BY BISULFITE-SEQUENCING METHOD
  • TOOLS FOR METHYLOMICS BY BISULFITE-MICROARRAY METHOD
  • TOOLS FOR METHYLOMICS BY ENRICHMENT-BASED METHOD
  • DNA METHYLATION DATA VISUALIZATION
  • DNA METHYLOMICS IN ORAL CANCER
  • DNA METHYLATION BIOMARKER FOR OSCC
  • ADVANCEMENT IN DNA METHYLATION STUDY IN OSCC
  • CONCLUSION
  • REFERENCES
  • 15 - COMPUTATIONAL EPIGENETICS FOR BREAST CANCER
  • INTRODUCTION
  • DNA METHYLATION IN BREAST CANCER
  • HISTONE MODIFICATION IN BREAST CANCER
  • NONCODING RNA REGULATION IN BREAST CANCER
  • EPIGENETIC DATABASES
  • EPIGENETIC TOOLS IN CANCER
  • FUTURE DIRECTIONS
  • REFERENCES
  • 16 - INTEGRATIVE EPIGENOMICS OF PROSTATE CANCER
  • PROSTATE CANCER: AN OVERVIEW
  • GENOMIC ALTERATIONS IN PCA
  • EPIGENOMIC ALTERATIONS IN PCA
  • DNA METHYLATION
  • DNA HYDROXYMETHYLATION
  • HISTONE MODIFICATIONS
  • MICRORNA AND LONG NONCODING RNA
  • RATIONALE FOR INTEGRATIVE ANALYSIS
  • EMERGING INTEGRATIVE ANALYSIS TOOLS UTILIZED IN PCA
  • FUTURE DIRECTIONS AND POTENTIAL APPLICATIONS FOR PCA
  • CONCLUDING REMARKS
  • REFERENCES
  • 17 - NETWORK ANALYSIS OF EPIGENETIC DATA FOR BLADDER CANCER
  • INTRODUCTION
  • MATERIALS AND METHODS
  • DATA PREPROCESSING OF OMICS DATA
  • CONSTRUCTION OF THE STOCHASTIC REGRESSION MODELS FOR THE IGEN SYSTEM
  • IDENTIFICATION OF THE TF REGULATORY ABILITY AIJ, THE MIRNA REPRESSION ABILITY CLI, AND THE PROTEIN INTERACTION ABILITY DJK ...
  • PRINCIPAL GENOME-WIDE NETWORK PROJECTION
  • DESIGN OF A MULTIPLE DRUG COMBINATION WITH MINIMAL SIDE EFFECTS FOR THE TREATMENT OF BLADDER CANCER
  • RESULTS AND DISCUSSION
  • CONSTRUCTION OF IGEN
  • PROJECTION OF THE CORE NETWORK BIOMARKERS INTO BIOLOGICAL PROCESSES AND SIGNALING PATHWAYS TO INVESTIGATE CARCINOGENIC MECH ...
  • THE IMPACT OF AGING, SMOKING, AND MIRNA AND EPIGENETIC REGULATION ON BLADDER CARCINOGENESIS THROUGH THE CORE NETWORK BIOMARKERS
  • MIR1-2 AND MIR200B MEDIATE THE REDUCTION OF CELL PROLIFERATION AND METASTASIS THROUGH KPNA2 AND ECT2, RESPECTIVELY
  • THE SMOKING-RELATED PROTEIN HSP90AA1 AND DNA METHYLATION OF ECT2 MEDIATE THE METASTASIS OF BLADDER CANCER
  • FUNCTIONAL MODULE NETWORK ANALYSIS IN BLADDER CARCINOGENESIS
  • TWO SEPARATE DRUG COMBINATIONS FOR TREATING STAGE 1 AND STAGE 4 BLADDER CANCER CELLS WITH MINIMAL SIDE EFFECTS
  • CONCLUSION
  • REFERENCES
  • FURTHER READING
  • 18 - EPIGENOME-WIDE ANALYSIS OF DNA METHYLATION IN COLORECTAL CANCER
  • INTRODUCTION
  • APPROACHES TO ANALYZE DNA METHYLATION IN COLORECTAL CANCER
  • EPIGENOME-WIDE ANALYSIS OF DNA METHYLATION IN COLORECTAL CANCER
  • DNA METHYLATION BIOMARKERS IN COLORECTAL CANCER
  • BLOOD-BASED DNA METHYLATION BIOMARKERS
  • STOOL-BASED DNA METHYLATION BIOMARKERS
  • PROGNOSTIC BIOMARKERS
  • COMPUTATIONAL TOOLS FOR DNA METHYLATION
  • WORKFLOW FOR DNA METHYLATION ANALYSIS IN CRC
  • CONCLUSION
  • ACKNOWLEDGMENT
  • REFERENCES
  • FURTHER READING
  • 19 - INTEGRATIVE OMIC ANALYSIS OF NEUROBLASTOMA
  • INTRODUCTION
  • NEUROBLASTOMA
  • OMICS: GENOMICS, TRANSCRIPTOMICS, PROTEOMICS, EPIGENOMICS, AND METABOLOMICS
  • INTEGRATIVE OMICS
  • TOOLS FOR NGS DATA ANALYSIS AND INTEGRATIVE OMICS
  • WORKFLOW
  • NEUROBLASTOMA OMICS
  • Genome
  • TRANSCRIPTOME AND EPIGENOME
  • INTEGRATIVE OMICS
  • NETWORK MODELING, REVERSE ENGINEERING MODELING, AND DYNAMIC MODELING
  • MACHINE LEARNING-BASED MODELING
  • SUMMARY AND FUTURE DIRECTIONS
  • REFERENCES
  • 20 - COMPUTATIONAL ANALYSIS OF EPIGENETIC MODIFICATIONS IN MELANOMA
  • INTRODUCTION
  • DNA MODIFICATIONS
  • 5-Methylcytosine
  • Reduced Representation Bisulfite Sequencing (RRBS)
  • 5-Hydroxymethylcytosine
  • HISTONE MODIFICATIONS AND CHROMATIN STATES
  • Chromatin-Immunoprecipitation Followed by Sequencing (ChIP-Seq)
  • HIGHER-ORDER CHROMATIN STRUCTURE
  • Chromosome Conformation Capture Based Methods
  • NUCLEOSOME POSITIONING
  • ATAC-Seq
  • FUTURE PERSPECTIVE
  • REFERENCES
  • 21 - DNA METHYLOME OF ENDOMETRIAL CANCER
  • INTRODUCTION
  • MOLECULAR SIGNALING PATHWAYS OF ENDOMETRIAL CARCINOMA
  • PI3/AKT/MTOR
  • MAPK/ERK
  • WNT/ß-CATENIN
  • VEGF/VEGFR
  • HER-2/NEU
  • EPIGENETIC ALTERNATIONS IN ENDOMETRIAL CARCINOMA
  • ENZYME DIGESTION-BASED METHODS
  • AFFINITY ENRICHMENT-BASED METHODS
  • BISULFITE CONVERSION-BASED METHODS
  • DNA MISMATCH REPAIR GENES
  • STEROID RECEPTOR GENES
  • TUMOR SUPPRESSOR GENES
  • OTHER RELATED GENES
  • MICRORNA ABERRANT METHYLATION IN ENDOMETRIAL CARCINOMA
  • TS-MIRNAS INVOLVED IN ENDOMETRIAL CANCER WITH THEIR FUNCTION INCLUDING MIR-129-2, MIR-152, MIR-124, MIR-126, MIR-137, AND M ...
  • DNA METHYLATION MACHINERY IN ENDOMETRIUM
  • APPLICATION OF DNA HYPERMETHYLATION FOR TREATMENT
  • FUTURE DIRECTS AND CONCLUSION
  • REFERENCES
  • FURTHER READING
  • 22 - EPIGENETICS AND EPIGENOMICS ANALYSIS FOR AUTOIMMUNE DISEASES
  • STUDY DESIGN AND DATA ACQUISITION METHODS
  • MICROARRAY-BASED DETECTION
  • NEXT-GENERATION SEQUENCING
  • EPIGENETIC CHANGES IN AUTOIMMUNE DISEASES
  • RHEUMATOID ARTHRITIS
  • SYSTEMIC LUPUS ERYTHEMATOSUS
  • MULTIPLE SCLEROSIS
  • TYPE 1 DIABETES
  • ANALYZING EPIGENETIC CHANGES IN AUTOIMMUNE DISEASES
  • DNA METHYLATION
  • Data Analysis Post Immunoprecipitation Studies
  • Data Analysis Post Bisulfite Treatment
  • Data Analysis Post Next-Generation Sequencing
  • HISTONE MODIFICATION ANALYSIS
  • MIRNA AND TARGETS PREDICTION
  • EPIGENETIC DATABASES
  • HISTOME
  • METHYLOMEDB
  • METHBASE
  • MIRWALK2.0
  • ROADMAP EPIGENOMICS
  • CONCLUSION
  • REFERENCES
  • 23 - COMPUTATIONAL EPIGENETICS IN LUNG CANCER
  • INTRODUCTION
  • CONCEPTUAL BASIS OF THE OBJECTIVE CLUSTERING INDUCTIVE TECHNOLOGY
  • AFFINITY METRIC AND CLUSTERING QUALITY CRITERIA TO ESTIMATE THE PROXIMITY OF GENE EXPRESSION PROFILES
  • SIMULATION OF THE OBJECTIVE CLUSTERING PROCESS USING LUNG CANCER PATIENTS' GENE EXPRESSION PROFILES
  • PRACTICAL IMPLEMENTATION OF SOTA AND DBSCAN CLUSTERING ALGORITHMS WITHIN THE FRAMEWORK OF THE OBJECTIVE CLUSTERING INDUCTIV ...
  • RESULTS OF THE SIMULATION AND DISCUSSION
  • HYBRID MODEL OF CLUSTER-BICLUSTER ANALYSIS OF GENE EXPRESSION PROFILES
  • CONCLUSIONS
  • REFERENCES
  • Index
  • A
  • B
  • C
  • D
  • E
  • F
  • G
  • H
  • I
  • J
  • K
  • L
  • M
  • N
  • O
  • P
  • Q
  • R
  • S
  • T
  • U
  • V
  • W
  • X
  • Z
  • Back Cover

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