Wolfgang Huber is a renowned bioinformatician and statistician. He has made significant contributions to the field of computational biology, particularly in the analysis of high-throughput sequencing data. Huber has worked at several prestigious research institutions, including the European Molecular Biology Laboratory (EMBL) and the German Cancer Research Center. Susan Holmes is a professor of statistics at Stanford University. Her research focuses on developing statistical methods for analyzing complex biological data. Holmes has co-authored numerous influential papers and has been a key figure in promoting the use of modern statistical techniques in biology.
Modern Statistics for Modern Biology by Wolfgang Huber and Susan Holmes offers a comprehensive guide to statistical analysis in the field of biology. The book covers a wide range of topics including experimental design, hypothesis testing, regression analysis, and statistical programming in R. It provides practical examples and exercises to help biologists apply statistical methods to their own research.
Modern Statistics for Modern Biology by Susan Holmes is a comprehensive guide that introduces biologists to the essential statistical techniques and computational tools needed for analyzing and interpreting biological data. The book covers topics such as data visualization, hypothesis testing, regression analysis, and machine learning, all with a focus on real-world biological applications. It provides clear explanations and practical examples, making it an invaluable resource for biologists looking to enhance their statistical skills.
Biologists and life scientists looking to apply statistical methods to their research
Graduate students or researchers who want to learn how to analyze biological data using modern statistical techniques
Professionals in the field of bioinformatics or computational biology seeking to enhance their statistical skills