The Analysis of Biological Data provides students with a practical foundation of statistics for biology students. Every chapter has several biological or medical examples of key concepts, and each example is prefaced by a substantial description of the biological setting. The emphasis on real and interesting examples carries into the problem sets where students have dozens of practice problems based on real data. The third edition features over 200 new examples and problems. These include new calculation practice problems, which guide the student step by step through the methods, and a greater number of examples and topics come from medical and human health research. Every chapter has been carefully edited for even greater clarity and ease of use. All the data sets, R scripts for all worked examples in the book, as well as many other teaching resources, are available to qualified instructors (see below).
This book is the first of its kind to bring together two important research areas, soft computing and bioinformatics, in order to demonstrate how the tools and techniques in the former can be used for efficiently solving several problems in ...
This volume also includes a section on advanced procedures and a chapter outlining algorithms and the art of programming using R. This second edition has been revised to be current with the versions of R software released since the book’s ...
This book is suitable as a resource for researchers in computer science, biology, bioinformatics, advanced biochemistry, and the life sciences, and also serves as an ideal reference text for graduate-level courses in bioinformatics and ...
The book includes feedback the editor received from students studying at both undergraduate and graduate levels, and from her peers.
... with different fill patterns or colors, at each level of the first grouping variable (Figure 19.2). A variation on bar graphs sometimes used in business presentations is called a pictogram (Snee & Pfeifer 1983), where the bar is ...
Some multivariate methods have been specifically designed to decompose the variability between codon usage within the differently abundantamino acids (Grantham et al., 1981; Perrière and Thioulouse, 2002), and this enables discovery of ...
This richly illustrated book provides an overview of the design and analysis of experiments with a focus on non-clinical experiments in the life sciences, including animal research.
Kniha je zaměřena na regresní modely, konkrétně jednorozměrné zobecněné lineární modely (GLM).
Introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, using real-world biological and medical examples.
Simple data analysis for biologists