Probabilistic Methods for Bioinformatics 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


Probabilistic Methods for Bioinformatics

简体网页||繁体网页
Richard E. Neapolitan 作者
Morgan Kaufmann
译者
2009-4-17 出版日期
424 页数
USD 76.95 价格
Hardcover
丛书系列
9780123704764 图书编码

Probabilistic Methods for Bioinformatics 在线电子书 图书标签: 算法  生物信息   


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Probabilistic Methods for Bioinformatics 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Probabilistic Methods for Bioinformatics 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Probabilistic Methods for Bioinformatics 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



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讲的很明白,结合了生物学背景和算法,并给出了详细的例子与解答,非常值得一读

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讲的很明白,结合了生物学背景和算法,并给出了详细的例子与解答,非常值得一读

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讲的很明白,结合了生物学背景和算法,并给出了详细的例子与解答,非常值得一读

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讲的很明白,结合了生物学背景和算法,并给出了详细的例子与解答,非常值得一读

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讲的很明白,结合了生物学背景和算法,并给出了详细的例子与解答,非常值得一读

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Probabilistic Methods for Bioinformatics 在线电子书 图书描述

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.

Unique coverage of probabilistic reasoning methods applied to bioinformatics data--those methods that are likely to become the standard analysis tools for bioinformatics.

Shares insights about when and why probabilistic methods can and cannot be used effectively;

Complete review of Bayesian networks and probabilistic methods with a practical approach.

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