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Titlebook: Mathematical Principles in Bioinformatics; Stephen S.-T. Yau,Xin Zhao,Hongyu Yu Textbook 2023 The Editor(s) (if applicable) and The Author

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發(fā)表于 2025-3-21 18:08:34 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Mathematical Principles in Bioinformatics
編輯Stephen S.-T. Yau,Xin Zhao,Hongyu Yu
視頻videohttp://file.papertrans.cn/627/626517/626517.mp4
概述Focuses on alignment-free methods in sequence comparison, which are neglected in many books on bioinformatics.Introduces the method to form a practical genome/protein space and proposes the convex hul
叢書名稱Interdisciplinary Applied Mathematics
圖書封面Titlebook: Mathematical Principles in Bioinformatics;  Stephen S.-T. Yau,Xin Zhao,Hongyu Yu Textbook 2023 The Editor(s) (if applicable) and The Author
描述.This textbook introduces bioinformatics to students in mathematics with no biology background assumed and it provides solid mathematical tools for biology students along with an understanding of how to implement them in bioinformatics problems. In addition to the basics, the text offers new approaches to understanding biological sequences. The concise presentation distinguishes itself from others on the subject, discussing and providing principles that relate to current open problems in bioinformatics as well as considering a variety of models. The convex hull principle is highlighted, opening a new interdisciplinary research area at the intersection of biology, mathematics, and computer science. Prerequisites include first courses in linear algebra, probability and statistics, and mathematical analysis. Researchers in mathematics, biology, and math-biology, will also find aspects of this text useful. . This textbook is written based on the authors‘ research works that have been published in various journals along with the lecture notes used when teaching bioinformatics courses at the University of Illinois at Chicago and at Tsinghua University. ?The content may be divided into tw
出版日期Textbook 2023
關(guān)鍵詞bioinformatics; Alignment-free methods; Principles in biology; phylogenetic analysis; natural vector met
版次1
doihttps://doi.org/10.1007/978-3-031-48295-3
isbn_softcover978-3-031-48297-7
isbn_ebook978-3-031-48295-3Series ISSN 0939-6047 Series E-ISSN 2196-9973
issn_series 0939-6047
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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發(fā)表于 2025-3-21 20:38:50 | 只看該作者
Sequence Alignment,uence analysis. When we establish a connection between a newly discovered sequence and one for which certain information (such as structure or function) is available, we open the possibility of applying the known information, to some extent, to the new sequence as well. Sequences that share a common
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發(fā)表于 2025-3-22 01:37:54 | 只看該作者
The Time-Frequency Spectral Analysis and Applications in Bioinformatics, employing diverse time-frequency representations. The notion that a time series exhibits repetitive or predictable behaviors over time holds pivotal significance, distinguishing time series analysis from classical statistics analyses. The consistency within a time series finds expression in the fre
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發(fā)表于 2025-3-22 06:14:25 | 只看該作者
Graphical Representation of Sequences and Its Application,quences provides a simple way of viewing, sorting, and comparing sequence similarity. In this chapter, we introduce two directions to construct graphical representation for biological sequences. The first direction is by curves without degeneracy and the second one is by Chaos Game Representation.
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發(fā)表于 2025-3-22 12:07:17 | 只看該作者
The Development and Applications of the Natural Vector Method,d discuss its properties and advantages. Then we will apply this method together to several biological problems. Finally, we show that the natural vector method can be generalized to produce some other alignment-free methods.
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