Short description This practical introduction clearly presents the underlying statistical concepts and techniques critical for successful use of bioinformatics tools in biomedical research without requiring an advanced background in math/statistics.
From the contents Chapter 1: Road to Statistical Bioinformatics
Chapter 2: Probability concepts and distributions for analyzing large biological data
Chapter 3: Quality control of high throughput biological data
Chapter 4: Statistical testing and significance for large biological data analysis
Chapter 5: Advance statistical modeling and inference on large biological data
Chapter 6: Clustering: unsupervised learning in large screening biological data
Chapter 7: Classification: supervised learning in large screening biological data
Chapter 8: Multi-dimensional analysis and visualization on large biological data
Chapter 9: Experimental designs on high throughput biological experiments
Chapter 10: Statistical resampling techniques for large biological data analysis
Chapter 11: Statistical network analysis for biological systems and pathways
Chapter 12: Advances in current statistical genetics and association studies
Chatper 13: R and Bioconductor packages in bioinformatics
