Bioinformatics

Author: [French] Pierre Baldi
Publisher:
Publish Date: 2003-07-01
Features: The author not only shows us a and the tools to build the current biinformatics mansion, but more importantly, the author guides us through the process of how to build this mansion and how to set up the "scaffolding," which is very important whether for repairing this mansion or building a new one. This book introduces the main content of machine learning methods and their applications in biological data processing. Among them, the theoretical foundation of machine learning technology - the Bayesian probability system is introduced in detail, and on this basis, it focuses on a detailed analysis of methods such as neural networks, hidden Markov models, and probabilistic graphical models in biinformatics. The book especially lists a chapter introducing DNA microarrays and gene expression, as well as the analysis methods of related data. This book is mainly aimed at two groups of readers. One is biology and biochemistry researchers who want to understand algorithms based on data processing; the other is scholars in fields such as physics, mathematics, statistics, computer science, who want to know the application of machine learning methods in molecular biology research.