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7 produkter
7 produkter
3 652 kr
Skickas inom 10-15 vardagar
Over the last ten years the introduction of computer intensive statistical methods has opened new horizons concerning the probability models that can be fitted to genetic data, the scale of the problems that can be tackled and the nature of the questions that can be posed. In particular, the application of Bayesian and likelihood methods to statistical genetics has been facilitated enormously by these methods. Techniques generally referred to as Markov chain Monte Carlo (MCMC) have played a major role in this process, stimulating synergies among scientists in different fields, such as mathematicians, probabilists, statisticians, computer scientists and statistical geneticists. Specifically, the MCMC "revolution" has made a deep impact in quantitative genetics. This can be seen, for example, in the vast number of papers dealing with complex hierarchical models and models for detection of genes affecting quantitative or meristic traits in plants, animals and humans that have been published recently.This book, suitable for numerate biologists and for applied statisticians, provides the foundations of likelihood, Bayesian and MCMC methods in the context of genetic analysis of quantitative traits. Most students in biology and agriculture lack the formal background needed to learn these modern biometrical techniques. Although a number of excellent texts in these areas have become available in recent years, the basic ideas and tools are typically described in a technically demanding style, and have been written by and addressed to professional statisticians. For this reason, considerable more detail is offered than what may be warranted for a more mathematically apt audience. The book is divided into four parts. Part I gives a review of probability and distribution theory. Parts II and III present methods of inference and MCMC methods. Part IV discusses several models that can be applied in quantitative genetics, primarily from a bayesian perspective. An effort has been made to relate biological to statistical parameters throughout, and examples are used profusely to motivate the developments.
3 652 kr
Skickas inom 10-15 vardagar
Over the last ten years the introduction of computer intensive statistical methods has opened new horizons concerning the probability models that can be fitted to genetic data, the scale of the problems that can be tackled and the nature of the questions that can be posed.
Del 7 - Doctor Who Target Novels – Classic Era
Doctor Who: The Witchfinders (Target Collection)
Häftad, Engelska, 2021
108 kr
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‘I am an expert on witchcraft, Doctor, but I wish to learn more. Before you die, I want answers.’The TARDIS lands in the Lancashire village of Bilehurst Cragg in the 17th century, and the Doctor, Ryan, Graham and Yaz soon become embroiled in a witch trial run by the local landowner. Fear stalks the land, and the arrival of King James I only serves to intensify the witch hunt. But the Doctor soon realises there is something more sinister than paranoia and superstition at work. Tendrils of living mud stir in the ground and the dead lurch back to horrifying life as an evil alien presence begins to revive. The Doctor and her friends must save not only the people of Bilehurst Cragg from the wakening forces, but the entire world
Del 8 - Doctor Who Target Novels – Classic Era
Doctor Who: Dalek (Target Collection)
Häftad, Engelska, 2021
170 kr
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‘The entire Dalek race, wiped out in one second. I watched it happen. I made it happen!’The Doctor and Rose arrive in an underground vault in Utah in the near future. The vault is filled with alien artefacts. Its billionaire owner, Henry van Statten, even has possession of a living alien creature, a mechanical monster in chains that he has named a Metaltron. Seeking to help the Metaltron, the Doctor is appalled to find it is in fact a Dalek – one that has survived the horrors of the Time War just as he has. And as the Dalek breaks loose, the Doctor is brought back to the brutality and desperation of his darkest hours spent fighting the creatures of Skaro… this time with the Earth as their battlefield.
181 kr
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"I think if you can get a kid reading for pleasure, not because it's work, but actually reading for pleasure, it's a great step forward. It can start with me, you know, start with Dicks and work its way up to Dickens - as long as you get them reading." - Terrance DicksFor over 50 years, Terrance Dicks was the secret beating heart(s) of Doctor Who - from joining production of The Invasion in 1968 to his final short story in 2019. As the undisputed master of Doctor Who fiction, Terrance wrote 64 Target novels from his first commission in 1973 to his last, published in 1990. He helped introduce an entire generation to the pleasures of reading and writing, and his fans include Neil Gaiman, Sarah Waters, Mark Gatiss, Alastair Reynolds, Russell T Davies, Steven Moffat, Frank-Cottrell Boyce, and Robert Webb, among many others.This two-volume collection, features the very best of his Doctor Who novels as chosen by fans - from his first book, The Auton Invasion, to his masterwork, the 20th anniversary celebration story The Five Doctors, voted all-time favourite.This volume contains, complete and unabridged:DOCTOR WHO AND THE DALEK INVASION OF EARTHDOCTOR WHO AND THE ABOMINABLE SNOWMENDOCTOR WHO AND THE WHEEL IN SPACEDOCTOR WHO AND THE AUTON INVASIONDOCTOR WHO AND THE DAY OF THE DALEKS
1 690 kr
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The MarkDown interface allows the students to implement the code on their own computer, contributing to a better understanding of the underlying theory. Part I presents methods of inference based on likelihood and Bayesian methods, including computational techniques for fitting likelihood and Bayesian models.
1 795 kr
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This book provides an introduction to computer-based methods for the analysis of genomic data. Breakthroughs in molecular and computational biology have contributed to the emergence of vast data sets, where millions of genetic markers for each individual are coupled with medical records, generating an unparalleled resource for linking human genetic variation to human biology and disease. Similar developments have taken place in animal and plant breeding, where genetic marker information is combined with production traits. An important task for the statistical geneticist is to adapt, construct and implement models that can extract information from these large-scale data. An initial step is to understand the methodology that underlies the probability models and to learn the modern computer-intensive methods required for fitting these models. The objective of this book, suitable for readers who wish to develop analytic skills to perform genomic research, is to provide guidance to take this first step.This book is addressed to numerate biologists who may lack the formal mathematical background of the professional statistician. For this reason, considerably more detailed explanations and derivations are offered. Examples are used profusely and a large proportion involves programming with the open-source package R. The code needed to solve the exercises is provided and it can be downloaded, allowing students to experiment by running the programs on their own computer.Part I presents methods of inference and computation that are appropriate for likelihood and Bayesian models. Part II discusses prediction for continuous and binary data using both frequentist and Bayesian approaches. Some of the models used for prediction are also used for gene discovery. The challenge is to find promising genes without incurring a large proportion of false positive results. Therefore, Part II includes a detour on the False Discovery Rate, assuming frequentist and Bayesian perspectives. The last chapter of Part II provides an overview of a selected number of non-parametric methods. Part III consists of exercises and their solutions. This second edition has benefited from many clarifications and extensions of themes discussed in the first edition.Daniel Sorensen holds PhD and DSc degrees from the University of Edinburgh and is an elected Fellow of the American Statistical Association. He was professor of Statistical Genetics at Aarhus University where, at present, he is professor emeritus.