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.

This 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.

Table of Contents

1. Bioinformatics for Life and Personal Genome Interpretation
   1. Bioinformatics for Life – Ju Han Kim
   2. Next-Generation Sequencing Technology and Personal Genome Data Analysis – Ju Han Kim
   3. Personal Genome Data Analysis – Ju Han Kim
   4. Personal Genome Interpretation and Disease Risk Prediction – Ju Han Kim
2. Advanced Microarray Data Analysis
   1. Advanced Microarray Data Analysis – Ju Han Kim
   2. Gene Expression Data Analysis – Ju Han Kim
   3. Gene Ontology and Biological Pathway-Based Analysis – Ju Han Kim
   4. Gene Set Approaches and Prognostic Subgroup Prediction – Ju Han Kim
   5. MicroRNA Data Analysis – Ju Han Kim
3. Network Biology, Sequence, Pathway and Ontology Informatics
   1. Network Biology, Sequence, Pathway and Ontology Informatics – Ju Han Kim
   2. Motif and Regulatory Sequence Analysis – Ju Han Kim
   3. Molecular Pathways and Gene Ontology – Ju Han Kim
   4. Biological Network Analysis – Ju Han Kim
4. SNPS, GWAS and CNVS, Informatics for Genome Variants
   1. SNPs, GWAS, CNVs: Informatics for Human Genome Variations – Ju Han Kim
   2. SNP Data Analysis – Ju Han Kim
   3. Metagenome and Epigenome, Basic Data Analysis
   4. Metagenome and Epigenome Data Analysis – Ju Han Kim
   5. Metagenome Data Analysis – Ju Han Kim
   6. Epigenome Database and Analysis Tools – Ju Han Kim
   7. Epigenome Data Analysis – Ju Han Kim

Author Biography

Professor. Ju Han Kim, Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul , South Korea.