Life in a post-genomic age has the promise to revolutionize our understanding of how our genes shape who we are, how our genome evolved, and how we function. There are new possibilities for an improved quality of life as we exploit new knowledge to design novel, more effective drugs. Central to these possibilities being realized is one of the most important information-gathering, data-mining, and knowledge-building tools in current research and healthcare development: bioinformatics. An Introduction to Bioinformatics introduces students to the immense power of bioinformatics as a set of scientific tools. The book explains how to access the data archives of genomes and proteins, and the kinds of questions these data and tools can answer: how to make inferences from the data archives, to make connections among them, and to derive useful and interesting predictions. Blending factual content with many opportunities for active learning, Introduction to Bioinformatics offers atruly reader-friendly way to get to grips with this subject, making it the ideal resource for anyone new to the field. Online Resource Centre: The Online Resource Centre features the following materials: For lecturers (password protected): DT Figures from the book available to download, to facilitate lecture slide preparation For students: DT Web link library of all URLs cited in the book, giving students ready access to these resources DT Guided tours of key websites, to help students get the most out of the vast array of information available online DT Hyperlinked bibliography - online links to articles referenced in the book, encouraging student engagement with the primary literature DT Links to PDB structures of all proteins cited in the book, to enable students to investigate the 3D structures of proteins in a visual, interactive way DT Data from the book in computer-readable form, which is available for instant use to facilitate hands-on learning by the student - Guidance to help students answer problems from the text, to support and encourage self-directed learning.