Genome Data Analysis

This textbook covers recent advances in genomics and bioinformatics, with examples of genome data analysis illustrating its relevance to real-world problems. It demonstrates basic data preprocessing, primary pattern analysis, and machine learning algorithms using R and Python for gene-expression microarrays, genotyping microarrays, next-generation sequencing data, epigenomic data, and biological network and semantic analyses. It also covers integrative genomic data analysis, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining, and integrated management of biomolecular databases. The textbook is intended for life scientists, medical scientists, statisticians, data processing researchers, engineers, and other beginners in bioinformatics.

Format: Paperback / softback
Length: 367 pages
Publication date: 10 May 2019
Publisher: Springer Verlag, Singapore

This comprehensive textbook delves into the latest advancements in genomics and bioinformatics, offering a wealth of examples showcasing the significance of genome data analysis in addressing real-world problems. By providing a solid foundation in basic data preprocessing techniques such as normalization and filtering, primary pattern analysis, and machine learning algorithms using R and Python, readers are equipped to handle diverse types of genome data, including gene-expression microarrays, genotyping microarrays, next-generation sequencing data, epigenomic data, and biological network and semantic analyses.

Furthermore, the textbook emphasizes the importance of integrative genomic data analysis, covering topics such as multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and the comprehensive management of biomolecular databases.

Designed with both beginners in bioinformatics and experts in the field in mind, this textbook serves as a valuable resource for those seeking to expand their knowledge and skills in this rapidly evolving subfield. Its clear explanations, practical examples, and extensive references make it an essential tool for researchers, scientists, and practitioners alike.

Weight: 806g
Dimension: 169 x 240 x 17 (mm)
ISBN-13: 9789811319419
Edition number: 1st ed. 2019