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Titlebook: Computational Genome Analysis; An Introduction Richard C. Deonier,Michael S. Waterman,Simon Tavar Textbook 2005 Springer-Verlag New York 20

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發(fā)表于 2025-3-21 16:23:55 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Computational Genome Analysis
副標(biāo)題An Introduction
編輯Richard C. Deonier,Michael S. Waterman,Simon Tavar
視頻videohttp://file.papertrans.cn/233/232321/232321.mp4
概述Describes the basic mathematics and statistics underlying computational genomics.Features free download of R software statistics package.Provides great crossover material that is interesting and acces
圖書(shū)封面Titlebook: Computational Genome Analysis; An Introduction Richard C. Deonier,Michael S. Waterman,Simon Tavar Textbook 2005 Springer-Verlag New York 20
描述.Computational Genome Analysis: An Introduction presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book is appropriate for a one-semester course for advanced undergraduate or beginning graduate students, and it can also introduce computational biology to computer scientists, mathematicians, or biologists who are extending their interests into this exciting field...This book features:..- Topics organized around biological problems, such as sequence alignment and assembly, DNA signals, analysis of gene expression, and human genetic variation..- Presentation of fundamentals of probability, statistics, and algorithms..- Implementation of computational methods with numerous examples based upon the R statistics package..- Extensive descriptions and explanations to complement the analytical development..- More than 100 illustrations and diagrams (some in color) to reinforce concepts and present key results from the primary literature..- Exercises at the end of chapter
出版日期Textbook 2005
關(guān)鍵詞Alignment; Analysis; DNA; algorithms; bioinformatics; clustering; computer; computer science; database; genom
版次1
doihttps://doi.org/10.1007/0-387-28807-4
isbn_softcover978-1-4419-3162-7
isbn_ebook978-0-387-28807-9
copyrightSpringer-Verlag New York 2005
The information of publication is updating

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Textbook 2005us examples based upon the R statistics package..- Extensive descriptions and explanations to complement the analytical development..- More than 100 illustrations and diagrams (some in color) to reinforce concepts and present key results from the primary literature..- Exercises at the end of chapter
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Words,of letters drawn from an alphabet, which in the case of DNA is the set of letters A, C, G, and T. A word of length . is called a “.-word” or “.-.”; we use these terms interchangeably. For example, individual bases are 1-tuples, dinucleotides are 2-tuples, and codons are triplets, or 3-tuples. GGGT is a 4-word or 4-tuple.
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發(fā)表于 2025-3-22 06:19:16 | 只看該作者
Word Distributions and Occurrences, Today, given a genome sequence, we could design PCR primers flanking the DNA of interest and by PCR could amplify just that segment. Prior to the development of rapid genomic sequencing technologies, the process was much more complicated.
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https://doi.org/10.1007/0-387-28807-4Alignment; Analysis; DNA; algorithms; bioinformatics; clustering; computer; computer science; database; genom
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978-1-4419-3162-7Springer-Verlag New York 2005
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