Computing is revolutionizing the practice of biology. This book, which assumes no prior computing experience, provides students with the tools to write their own Python programs and to understand fundamental concepts in computational biology and bioinformatics. Each major part of the book begins with a compelling biological question, followed by the algorithmic ideas and programming tools necessary to explore it: the origins of pathogenicity are examined using gene finding, the evolutionary history of sex determination systems is studied using sequence alignment, and the origin of modern humans is addressed using phylogenetic methods. In addition to providing general programming skills, this book explores the design of efficient algorithms, simulation, NP-hardness, and the maximum likelihood method, among other key concepts and methods. Easy-to-read and designed to equip students with the skills to write programs for solving a range of biological problems, the book is accompanied by numerous programming exercises, available at www.cs.hmc.edu/CFB.
Fault Covering Problems in Reconfigurable VLSI Systems describes the authors' recent research on reconfiguration problems for fault-tolerance in VLSI and WSI Systems. The book examines solutions to a number of reconfiguration problems. Efficient algorithms are given for tractable covering problems and general techniques are given for dealing with a large number of intractable covering problems. The book begins with an investigation of algorithms for the reconfiguration of large redundant memories. Next, a number of more general covering problems are considered and the complexity of these problems is analyzed. Finally, a general and uniform approach is proposed for solving a wide class of covering problems. The results and techniques described here will be useful to researchers and students working in this area. As such, the book serves as an excellent reference and may be used as the text for an advanced course on the topic.
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