Над 4 милиона заглавия на английски и други езици! Открийте новата си история още днес! Безплатна доставка за поръчки над 69.99€

Виж статуса на поръчката

Свържете се с нас

Probabilistic Methods for Bioinformatics:

Автор: Richard E Neapolitan

Език:

Корици: С меки корици

Издател: Elsevier Books

Наличност: Налично при издателя, по поръчка

Изпращаме след 28-34 дни

73.99 € 144.71 лв

The Bayesian network is one of the most important architectures for representing and reasoning with...

Информация за книгата

Автор

Richard E Neapolitan

Език

Английски език

Корици

Книга - С меки корици

Издадена

2009

страници

424

EAN

9780123704764

ISBN

0123704766

Enbook ID

04020691

Издател

Elsevier Books

Теглоt

905

Размери

198 x 243 x 32

Пълно описание

The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. "Probabilistic Methods for BioInformatics" explains the application of probability and statistics, in particular Bayesian networks, to genetics. This book provides background material on probability, statistics, and genetics, and then moves on to discuss Bayesian networks and applications to bioinformatics. Rather than getting bogged down in proofs and algorithms, probabilistic methods used for biological information and Bayesian networks are explained in an accessible way using applications and case studies. The many useful applications of Bayesian networks that have been developed in the past 10 years are discussed. Forming a review of all the significant work in the field that will arguably become the most prevalent method in biological data analysis, it has unique coverage of probabilistic reasoning methods applied to bioinformatics data - those methods that are likely to become the standard analysis tools for bioinformatics. It shares insights about when and why probabilistic methods can and cannot be used effectively. It includes a complete review of Bayesian networks and probabilistic methods with a practical approach.