了得網自然科學_生物信息學中的數學方法（英文版）

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生物信息學中的數學方法（英文版）
該商品所屬分類：自然科學 -> 數學
【市場價】	971-1408元
【優惠價】	607-880元
【作者】	王嘉松嚴明
【所屬類別】	圖書自然科學數學數學理論
【出版社】	科學出版社
【ISBN】	9787030369857
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內容介紹

開本：16開

紙張：膠版紙

包裝：平裝膠訂

是否套裝：否

國際標準書號ISBN：9787030369857

作者：王嘉松,嚴明

出版社：科學出版社

出版時間：2020年03月

內容簡介

全書采用將生物分子的符號序列首先變換為數值序列,之後,用數學方法從這些數列中提取生物信息.因而,先全面繫統介紹了DNA序列和蛋白質序列的數字及圖形表達後,就用幾種正交變換進行基因識別,蛋白質對比,以及用聚類分析來了解DNA和蛋白質的性質及進行分類.微數組,脂肪組是現成的大量生物數據,我們就用數理統計方法處理這些數據得到了某種癌癥的誘因.生物過程是動態過程,書中介紹了用微分方程和差分方程模型模擬這種過程的多種算法.由於生物數據部分缺失現像經常發生,*後介紹了迷失數據彌補的許多方法.

Contents
PREFACE
CHAPTER 1 SOME BIOLOGICAL CONCEPTS 1
1.1 Cell 1
1.2 Genetic Material: DNA，Gene and RNA 1
1.2.1 DNA 1
1.2.2 Gene 3
1.2.3 RNA 5
1.3 Protein and Amino Acids 7
1A Chromosome 9
1.5 Omics 10
1.5.1 Genomics 11
1.5.2 Microarray 11
1.5.3 Proteomics 11
1.5.4 Lipidomics 12
REFERENCES 13
CHAPTER 2 GRAPHICAL REPRESENTATIONS OF DNA SEQUENCE .14
2.1 Three-Dimension (3-D) Graphical Representation 14
2.2 2-D Graphical Representation 15
2.3 2-D Graphical Representations Without Degeneracy 17
2.4 Used a 1-D Numerical Representation of four Nucleotides to Construct a 2-D Graphical Representation of the DNA Sequence 22
REFERENCES 22
CHAPTER 3 NUMERICAL REPRESENTATIONS OF DNA SEQUENCE 24
3.1 4-D and 3-D Numerical Representations of a DNA Sequence 24
3.2 2-D Numerical Representations of a DNA Sequence 25
3.3 The Complex Numerical Representation 26
3.4 1-D Numerical Representations of four Nucleotides and 2-D Graphical Representation of a DNA Sequence 27
3.5 The Representations of Feature Vector， Genome Space and Matrix Representation of DNA Sequence 27
3.6 The Numerical Representation Based on Physical， Chemical and Structural Properties of DNA Sequence 29
3.6.1 The numerical representations based on some attribute equivalences of nucleotides 29
3.6.2 The representation of DNA by the inspiration from codon and the idea of three attribute equivalences 31
3.6.3 EIIP numerical representation for nucleotides 31
REFERENCES 32
CHAPTER 4 NUMERICAL REPRESENTATIONS OF PROTEIN 33
4.1 1-D Numerical and Graphical Representadons of the Amino Acid Sequence 33
4.2 2-D Numerical and Graphical Representations of the Amino Add Sequence 34
4.3 A 2-D Graphical Representation and Moment Vector Representation of Protein 41
4.4 3-D Numerical Representation of Protein 44
4.5 The 10-D Representation of an Amino Acid 45
4.6 The Vector and Matrix Representations of Protein Sequence and Protein Space . 46
4.7 Other Schemes of the Representation for Protein 46
REFERENCES 47
CHAPTER 5 PRACTICAL ORTHOGONAL TRANSFORM 49
5.1 Some Features and Algorithms for the Discrete Fourier Transform .49
5.1.1 Fourier transforms of the original sequence and its subsequence 49
5.1.2 The independency of fee Fourier transforms at several frequencies 52
5.1.3 The Fourier transform of symbolic sequence 53
5.1.4 Fourier transform of binary sequence 56
5.1.5 Several algorithms of Fourier transform 57
5.1.6 The properties of Fourier transform of real sequence 59
5.2 Wavelet Analysis 64
5.2.1 Introduction 64
5.2.2 Multiresolution analysis of a fimction by Haar scaling and wavelet function 65
5.2.3 Construction of wavelet systems 73
5.2.4 Mallet transform 78
REFERENCES 82
CHAPTER 6 IDENTIFYING PROTEIN-CODING REGIONS (EXONS) BY NUCLEOTIDE DISTRIBUTIONS 83
6.1 Portein Coding Regions Finding in DNA Sequence 83
6.1.1 Introduction 83
6.1.2 The stochastic simulation and several computing formulae 84
6.1.3 FEND algorithm，predicting protein coding regions from nucleotide distributions on the three positions of a DNA sequence 97
6.1.4 Performance evaluation of FEND algorithm 104
6.2 The Experiment for Distinguishing Exon and Intron Sequences by a Threshold 105
6.2.1 Motivation 105
6.2.2 Idea of distinguishing exon and intron sequences 106
6.2.3 Results and discussion 108
REFERENCES 109
CHAPTER 7 PROTEIN COMPARISON BY ORTHOGONAL TRANSFORMS
7.1 Protein Comparison by Discrete Fourier Transformation (DFT) 111
7.1.1 EIIP representation of protein sequence 111
7.1.2 Symmetry of discrete Fourier transform of real sequence 112
7.1.3 Cross-spectral function 112
7.2 Protein Comparison by Discrete Wavelet Transformation 115
7.2.1 Several techniques needed for DWT method 115
7.2.2 The performance of the DWT method 120
REFERENCES 124
CHAPTER 8 THE APPLICATION OF VECTOR REPRESENTATIONS TO BIOLOGICAL MOLECULE ANALYSIS 125
8.1 Use Feature Vector to Analyze DNA Sequences 125
8.1.1 Feature vector representation of DNA sequence 125
8.1.2 Comparing DNA sequences 126
8.2 A Protein Map and its Applications 129
8.2.1 Recalling a 2-D graphical representation and moment vector representation of protein 129
8.2.2 Protein map and cluster analysis 129
8.3 An Appendix: Introduction to Cluster Analysis 133
REFERENCES 137
CHAPTER 9 THE STATISTICS ANALYSIS OF LARGE AMOUNT OF EXPERIMENTAL DATA 138
9.1 A Way to Process Microarray Data 138
9.1.1 Data form 138
9.1.2 Microarray data set 140
9.1.3 Preliminary filtering 140
9.1.4 Assessing normalization 141
9.1.5 Hypothesis test 144
9.1.6 Conclusion 146
9.2 The Statistical Analysis of a Set ofLipidomics Data 146
9.2.1 Introduction 146
9.2.2 Statistical techniques of initial data processing 148
9.2.3 Initial data arrangement 150
9.2.4 Hypothesis testing analysis 154
REFERENCE

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