LEADER 01917nam 2200409Ia 450 001 996387325103316 005 20200824132727.0 035 $a(CKB)4940000000082224 035 $a(EEBO)2240867213 035 $a(OCoLC)ocm15994864e 035 $a(OCoLC)15994864 035 $a(EXLCZ)994940000000082224 100 $a19870618d1666 uy | 101 0 $aeng 135 $aurbn||||a|bb| 200 10$aNewes from the stars, or, An ephemeris for the year of mans redemption by Jesus Christ, 1666$b[electronic resource] $ewherein you have the motions and eclipses of the sunne and moon, the two great lights of heaven : with the mutual aspects of the planets, and observations thereupon : together with astrological judgments upon the several eclipses, and ingress of the sun into the æquinoctial and solstitial points of heaven : as also some observations and predictions upon the comets seen in 1664 and in 1665 : wherein is discovered those various actions and designs which are intended by the heavens to be on foot in most parts of Europe this present year 1666 /$fcalculated for the meridian of London by William Andrews .. 210 $aLondon $cPrinted by Tho. 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Yau, Xin Zhao, Kun Tian, Hongyu Yu 205 $a1st ed. 2023. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2023. 215 $a1 online resource (177 pages) 225 1 $aInterdisciplinary Applied Mathematics,$x2196-9973 ;$v58 311 08$aPrint version: Yau, Stephen S. -T. Mathematical Principles in Bioinformatics Cham : Springer,c2024 9783031482946 327 $aPreface -- 1 Biological Overview -- 2 Bioinformatics Databases -- 3 Sequence Alignment -- 4 The Time-Frequency Spectral Analysis and Applications in Bioinformatics -- 5 Graphical Representation of Sequences and Its Application -- 6 The Development and Applications of the Natural Vector Method -- 7 Convex Hull Principle and Distinguishing Proteins from Arbitrary Amino Acid Sequences -- 8 New Features or Metric on Sequence Comparison -- References. 330 $aThis 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 beenpublished 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 two parts. The first part includes three chapters, introducing some basic concepts. Chapter 1 provides biological background in molecular biology for mathematicians. Chapter 2 describes biological databases that are commonly used. Chapter 3 is concerned with alignment methods including global/local alignment, heuristic alignment, and multiple alignment. The second part consisting of five chapters, describes several bioinformatics principles using a rigorous mathematical formulation. Chapter 4 introduces the time-frequency spectral principle and its applications in bioinformatics. In Chapters 5 and 6, two strategies are used, the graphical representation and the natural vector method, to represent biological sequences, and conduct sequence comparison and phylogenetic analysis without alignment. Chapter 7 presents the convex hull principle and shows how it can be used to mathematically determine whether a certain amino acid sequence can be a protein. The last chapter summarizes additional mathematical ideas relating to sequence comparisons, such as new feature vectors and metrics. This part focuses on the governing principle in biology and provides plenty of alignment-free methods, which cannot be found in any other book. 410 0$aInterdisciplinary Applied Mathematics,$x2196-9973 ;$v58 606 $aBioinformatics 606 $aMathematics 606 $aBioinformatics 606 $aApplications of Mathematics 615 0$aBioinformatics. 615 0$aMathematics. 615 14$aBioinformatics. 615 24$aApplications of Mathematics. 676 $a570.285 700 $aYau$b Stephen S. -T$01587106 701 $aZhao$b Xin$01287691 701 $aTian$b Kun$01338612 701 $aYu$b Hongyu$01587107 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910800117303321 996 $aMathematical Principles in Bioinformatics$93874454 997 $aUNINA