Titlebook: Statistical Methods in Bioinformatics; An Introduction Warren J. Ewens,Gregory R. Grant Textbook 20011st edition Springer-Verlag New York 2

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ce, immunization and response to vaccine administration as well as advancements in our understanding of growth and development with particular to the use of growth hormone therapy. Other new areas covered inclu978-1-4899-8978-9978-1-4614-5061-0

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1431-8776 ld be immediately accessible to the trained statistician. Sufficient mathematics background consists of courses in calculus and linear algebra. The basic biological concepts that a978-1-4757-3247-4Series ISSN 1431-8776 Series E-ISSN 2197-5671

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Textbook 20011st editionw areas of probability and statistics are being developed specifically to meet the needs of this area. There is now a necessity for a text that introduces probability and statistics in the bioinformatics context. This book also describes some of the main statistical applications in the field, includ

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The Analysis of One DNA Sequence,” One difficulty is that the locations of the fragments within the genome and with respect to each other are not generally known. However, if enough fragments are sequenced so that there will be many overlaps between them, the fragments can be matched up and assembled. This method is called “shotgun sequencing.”

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Probability Theory (i): One Random Variable,and thymine, respectively).. These sequences undergo change within any population over the course of many generations, as random mutations arise and become fixed in the population. Therefore, two rather different sequences may well derive from a common ancestor. Suppose we have two small DNA sequenc

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Statistics (i): An Introduction to Statistical Inference,ypothesis testing. Both of these are used extensively in bioinformatics. In this chapter we give a brief introduction to estimation and hypothesis testing ideas: A more complete discussion of both is given in Chapter 8.