Wednesday, April 24, 2019

Big Data Analysis for Bioinformatics and Biomedical Discoveries

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We are entering an era of Big Data. Big Data offer both unprecedented opportunities and overwhelming challenges. This book is intended to provide biologists, biomedical scientists, bioinformaticians, computer data analysts, and other interested readers with a pragmatic blueprint to the nuts and bolts of Big Data so they more quickly, easily, and effectively harness the power of Big Data in their ground-breaking biological discoveries, translational medical researches, and personalized genomic medicine.

Section i: Commonly Used Tools for Big Data Analysis
Chapter 1: Linux for Big Data Analysis
Chapter 2: Python for Big Data Analysis
Chapter 3: R for Big Data Analysis
Section ii: Next-Generation DNA Sequencing Data Analysis
Chapter 4: Genome-Seq Data Analysis
Chapter 5: RNA-Seq Data Analysis
Chapter 6: Microbiome-Seq Data Analysis
Chapter 7: miRNA-Seq Data Analysis
Chapter 8: Methylome-Seq Data Analysis
Chapter 9: ChIP-Seq Data Analysis
Section iii: Integrative and Comprehensive Big Data Analysis
Chapter 10: Integrating Omics Data in Big Data Analysis
Chapter 11: Pharmacogenetics and Genomics
Chapter 12: Exploring De-Identified Electronic Health Record Data with i2b2
Chapter 13: Big Data and Drug Discovery
Chapter 14: Literature-Based Knowledge Discovery
chapter 15: Mitigating High Dimensionality in Big Data

Author Details
"Shui Qing Ye"

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