Genome Data Analysis

Description

This textbook describes recent advances in genomics and bioinformatics and provides numerous examples of genome data analysis that illustrate its relevance to real world problems and will improve the reader’s bioinformatics skills. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine learning algorithms using R and Python are demonstrated for gene-expression microarrays, genotyping microarrays, next-generation sequencing data, epigenomic data, and biological network and semantic analyses. In addition, detailed attention is devoted to integrative genomic data analysis, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and integrated management of biomolecular databases. The textbook is primarily intended for life scientists, medical scientists, statisticians, data processing researchers, engineers, and other beginners in bioinformatics who are experiencing difficulty in approaching the field. However, it will also serve as a simple guideline for experts unfamiliar with the new, developing subfield of genomic analysis within bioinformatics. Front Matter ....Pages i-xvi Front Matter ....Pages 1-1 Bioinformatics for Life (Ju Han Kim)....Pages 3-15 Next-Generation Sequencing Technology and Personal Genome Data Analysis (Ju Han Kim)....Pages 17-31 Personal Genome Data Analysis (Ju Han Kim)....Pages 33-45 Personal Genome Interpretation and Disease Risk Prediction (Ju Han Kim)....Pages 47-75 Front Matter ....Pages 77-77 Advanced Microarray Data Analysis (Ju Han Kim)....Pages 79-93 Gene Expression Data Analysis (Ju Han Kim)....Pages 95-120 Gene Ontology and Biological Pathway-Based Analysis (Ju Han Kim)....Pages 121-134 Gene Set Approaches and Prognostic Subgroup Prediction (Ju Han Kim)....Pages 135-157 MicroRNA Data Analysis (Ju Han Kim)....Pages 159-172 Front Matter ....Pages 173-173 Network Biology, Sequence, Pathway and Ontology Informatics (Ju Han Kim)....Pages 175-187 Motif and Regulatory Sequence Analysis (Ju Han Kim)....Pages 189-211 Molecular Pathways and Gene Ontology (Ju Han Kim)....Pages 213-232 Biological Network Analysis (Ju Han Kim)....Pages 233-246 Front Matter ....Pages 247-247 SNPs, GWAS, CNVs: Informatics for Human Genome Variations (Ju Han Kim)....Pages 249-260 SNP Data Analysis (Ju Han Kim)....Pages 261-280 GWAS Data Analysis (Ju Han Kim)....Pages 281-297 CNV Analysis (Ju Han Kim)....Pages 299-312 Front Matter ....Pages 313-313 Metagenome and Epigenome Data Analysis (Ju Han Kim)....Pages 315-323 Metagenome Data Analysis (Ju Han Kim)....Pages 325-337 Epigenome Database and Analysis Tools (Ju Han Kim)....Pages 339-352 Epigenome Data Analysis (Ju Han Kim)....Pages 353-367