Algorithms in bioinformatics : theory and implementation /: theory and implementation. (2021)

• Record Type: Book
• Further Information: Note: Paul A. Gagniuc.
• Authors: Gagniuc, Paul A
• Contents: Preface xv About the Companion Website xvii 1 The Tree of Life (I) 1 1.1 Introduction 1 1.2 Emergence of Life 1 1.2.1 Timeline Disagreements 3 1.3 Classifications and Mechanisms 4 1.4 Chromatin Structure 5 1.5 Molecular Mechanisms 9 1.5.1 Precursor Messenger RNA 9 1.5.2 Precursor Messenger RNA to Messenger RNA 10 1.5.3 Classes of Introns 10 1.5.4 Messenger RNA 10 1.5.5 mRNA to Proteins 11 1.5.6 Transfer RNA 12 1.5.7 Small RNA 12 1.5.8 The Transcriptome 13 1.5.9 Gene Networks and Information Processing 13 1.5.10 Eukaryotic vs. Prokaryotic Regulation 14 1.5.11 What Is Life? 14 1.6 Known Species 14 1.7 Approaches for Compartmentalization 15 1.7.1 Two Main Approaches for Organism Formation 16 1.7.2 Size and Metabolism 16 1.8 Sizes in Eukaryotes 16 1.8.1 Sizes in Unicellular Eukaryotes 17 1.8.2 Sizes in Multicellular Eukaryotes 17 1.9 Sizes in Prokaryotes 17 1.10 Virus Sizes 18 1.10.1 Viruses vs. the Spark of Metabolism 20 1.11 The Diffusion Coefficient 20 1.12 The Origins of Eukaryotic Cells 21 1.12.1 Endosymbiosis Theory 21 1.12.2 DNA and Organelles 22 1.12.3 Membrane-bound Organelles with DNA 23 1.12.4 Membrane-bound Organelles Without DNA 23 1.12.5 Control and Division of Organelles 24 1.12.6 The Horizontal Gene Transfer 24 1.12.7 On the Mechanisms of Horizontal Gene Transfer 25 1.13 Origins of Eukaryotic Multicellularity 26 1.13.1 Colonies Inside an Early Unicellular Common Ancestor 26 1.13.2 Colonies of Early Unicellular Common Ancestors 26 1.13.3 Colonies of Inseparable Early Unicellular Common Ancestors 1.13.4 Chimerism and Mosaicism 28 1.14 Conclusions 29 2 Tree of Life: Genomes (II) 31 2.1 Introduction 31 2.2 Rules of Engagement 31 2.3 Genome Sizes in the Tree of Life 32 2.3.1 Alternative Methods 33 2.3.2 The Weaving of Scales 33 2.3.3 Computations on the Average Genome Size 36 2.3.4 Observations on Data 38 2.4 Organellar Genomes 40 2.4.1 Chloroplasts 40 2.4.2 Apicoplasts 40 2.4.3 Chromatophores 42 2.4.4 Cyanelles 42 2.4.5 Kinetoplasts 42 2.4.6 Mitochondria 43 2.5 Plasmids 43 2.6 Virus Genomes 44 2.7 Viroids and Their Implications 46 2.8 Genes vs. Proteins in the Tree of Life 47 2.9 Conclusions 49 3 Sequence Alignment (I) 51 3.1 Introduction 51 3.2 Style and Visualization 51 3.3 Initialization of the Score Matrix 54 3.4 Calculation of Scores 57 3.4.1 Initialization of the Score Matrix for Global Alignment 57 3.4.2 Initialization of the Score Matrix for Local Alignment 62 3.4.3 Optimization of the Initialization Steps 65 3.4.4 Curiosities 66 3.5 Traceback 71 3.6 Global Alignment 75 3.7 Local Alignment 79 3.8 Alignment Layout 84 3.9 Local Sequence Alignment – The Final Version 87 3.10 Complementarity 91 3.11 Conclusions 97 4 Forced Alignment (II) 99 4.1 Introduction 99 4.2 Global and Local Sequence Alignment 100 4.2.1 Short Notes 100 4.2.2 Understanding the Technology 101 4.2.3 Main Objectives 102 4.3 Experiments and Discussions 102 4.3.1 Alignment Layout 106 4.3.2 Forced Alignment Regime 106 4.3.3 Alignment Scores and Significance 109 4.3.4 Optimal Alignments 110 4.3.5 The Main Significance Scores 110 4.3.6 The Information Content 110 4.3.7 The Match Percentage 112 4.3.8 Significance vs. Chance 113 4.3.9 The Importance of Randomness 113 4.3.10 Sequence Quality and the Score Matrix 114 4.3.11 The Significance Threshold 115 4.3.12 Optimal Alignments by Numbers 116 4.3.13 Chaos Theory on Sequence Alignment 116 4.3.14 Image-Encoding Possibilities 116 4.4 Advanced Features and Methods 117 4.4.1 Sequence Detector 117 4.4.2 Parameters 117 4.4.3 Heatmap 118 4.4.4 Text Visualization 123 4.4.5 Graphics for Manuscript Figures and Didactic Presentations 124 4.4.6 Dynamics 124 4.4.7 Independence 125 4.4.8 Limits 125 4.4.9 Local Storage 125 4.5 Conclusions 128 5 Self-Sequence Alignment (I) 129 5.1 Introduction 129 5.2 True Randomness 130 5.3 Information and Compression Algorithms 130 5.4 White Noise and Biological Sequences 131 5.5 The Mathematical Model 131 5.5.1 A Concrete Example 132 5.5.2 Model Dissection 133 5.5.3 Conditions for Maxima and Minima 136 5.6 Noise vs. Redundancy 137 5.7 Global and Local Information Content 137 5.8 Signal Sensitivity 138 5.9 Implementation 140 5.9.1 Global Self-Sequence Alignment 140 5.9.2 Local Self-Sequence Alignment 144 5.10 A Complete Scanner for Information Content 147 5.11 Conclusions 149 6 Frequencies and Percentages (II) 151 6.1 Introduction 151 6.2 Base Composition 152 6.3 Percentage of Nucleotide Combinations 152 6.4 Implementation 153 6.5 A Frequency Scanner 156 6.6 Examples of Known Significance 158 6.7 Observation vs. Expectation 160 6.8 A Frequency Scanner with a Threshold 161 6.9 Conclusions 163 7 Objective Digital Stains (III) 165 7.1 Introduction 165 7.2 Information and Frequency 166 7.3 The Objective Digital Stain 169 7.3.1 A 3D Representation Over a 2D Plane 173 7.3.2 ODSs Relative to the Background 177 7.4 Interpretation of ODSs 181 7.5 The Significance of the Areas in the ODS 183 7.6 Discussions 184 7.6.1 A Similarity Be
• Edition: 1st
• Publisher Details: Hoboken : John Wiley & Sons, Inc
• Publication Date: 2021
• Extent: 1 online resource, illustrations
• Subjects: 572.80285; Bioinformatics; Algorithms
• Languages: English
• ISBNs: 9781119697992; 9781119697954
• Related ISBNs: 9781119697961
• Notes: Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
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