Download e-book for kindle: Statistical Methods in Bioinformatics: An Introduction by Warren J. Ewens, Gregory R. Grant

By Warren J. Ewens, Gregory R. Grant

ISBN-10: 0387400826

ISBN-13: 9780387400822

Advances in pcs and biotechnology have had a tremendous effect at the biomedical fields, with vast outcomes for humanity. Correspondingly, new parts of chance and facts are being built particularly to fulfill the desires of this zone. there's now a need for a textual content that introduces chance and records within the bioinformatics context. This publication additionally describes a few of the major statistical purposes within the box, together with BLAST, gene discovering, and evolutionary inference, a lot of which has now not but been summarized in an introductory textbook layout. This booklet grew out of a necessity to coach bioinformatics to graduate scholars on the collage of Pennsylvania. while even if, it's equipped to attract a much wider viewers. specifically it's going to entice any biologist or machine scientist who desires to recognize extra in regards to the statistical equipment of the sector, in addition to to a knowledgeable statistician who needs to get involved in bioinformatics. the sooner chapters introduce the ideas of chance and information at an easy point, and should be available to scholars who've in basic terms had introductory calculus and linear algebra. Later chapters are instantly available to the knowledgeable statistician. just a easy figuring out of organic strategies is believed, and all innovations are defined whilst used or might be understood from the context. numerous chapters include fabric self reliant of that during different chapters, in order that the reader drawn to definite components can continue on to these components. Warren Ewens is Professor of Biology on the college of Pennsylvania. he's the writer of 2 books, inhabitants Genetics and Mathematical inhabitants Genetics, and has served at the editorial forums of Theoretical inhabitants Biology, GENETICS, continuing of the Royal Society B and SIAM magazine in Mathematical Biology. He was once lately provided the Gold Medal of the Australian Statistical Society and elected as Fellow of the Royal Society. His learn pursuits are in evolutionary inhabitants genetics, linkage research for human ailments, and bioinformatics. Gregory furnish is a bioinformatics researcher on the collage of Pennsylvania within the Computational Biology and Informatics Laboratory (CBIL), the place he has been when you consider that 1998. In 1995 he obtained a Ph.D. in arithmetic from the college of Maryland and in 1999 a Masters in machine technological know-how from the college of Pennsylvania. His examine pursuits are in bioinformatics typically and particularly within the statistical research of gene expression information and value trying out equipment for IBD-mapping.

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2 ...... 13. The normal approximation to the binomial random variable with p = 14 and n = 20. (the only case where the binomial probability distribution is symmetric) the approximation is good even for n as small as 20, as is shown in an example below. The closer p is to zero or one, the further the binomial distribution is from being symmetric, and the larger n must be for the normal distribution to fit the binomial distribution well.

G. clicks on a geiger counter). 1. 8 Approximations While the probability distributions described above arise frequently in applications, there are also many cases where the random variable of interest does not have one of these distributions. Sometimes the distribution of the random variable is complicated and might not be easily calculated. In such cases this distribution is often approximated by one of the distributions described above. If this is done it is important to be able to place an upper bound on the error involved in the approximation.

15. Examples of the density function of a gamma distribution with λ = 1 and k = 21 , 1, 2, 3. and is given by the sum of k Poisson distribution terms. 3. When k is not an integer, no simple expression exists for the cumulative distribution function of the gamma distribution.

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Statistical Methods in Bioinformatics: An Introduction by Warren J. Ewens, Gregory R. Grant

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