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The massive research effort known as the Human Genome Project is an attempt to record the sequence of the three trillion nucleotides that make up the human genome and to identify individual genes within this sequence. While the basic effort is of course a biological one, the description and classification of sequences also lend themselves naturally to mathematical and statistical modeling. This short textbook on the mathematics of genome analysis presents a brief description of several ways in which mathematics and statistics are being used in genome analysis and sequencing. It will be of interest not only to students but also to professional mathematicians curious about the subject.
Preface; 1. Decomposing DNA; 2. Recomposing DNA; 3. Sequence statistics; 4. Sequence comparison; 5. Spatial structure and dynamics of DNA; Bibliography; Index.
'! a suitable textbook for a mathematics course aimed at raising awareness of the challenges that are posed by computational biology. It is also good first reading for mathematics students and professionals who want to get an idea of the exciting mathematical problems in the analysis of biological sequences.' Ralf Bundschuh, Physics Today '! a nice introduction to mathematical and statistical problems in genome analysis ! this text is a highly welcome and valuable enhancement of the existing literature in the field. apart from covering new grounds, the author explains some of the more recent ideas ! with great expertise. the exposition captivates by its systematic clarity, indicated profundity, necessary rigor, and masterly conciseness ! this book will rank among the most important monographs on abelian varieties and theta functions'. Zentralblatt fur Mathematic 'The American Joint Policy Board for Mathematics has chosen the role of mathematics in analysing and understanding the data arising from the Human Genome Project as the theme for Mathematics Awareness Month 2002, . Percus' state of the art snapshot of what is involved in unravelling this 'cunning'st pattern of excelling nature' (Othello, Act 5, Scene 2) could thus hardly be more timely.' The Mathematical Gazette