Bioinformatics : sequence alignment and Markov models

GET FULLY UP-TO-DATE ON BIOINFORMATICS-THE TECHNOLOGY OF THE 21ST CENTURY Bioinformatics showcases the latest developments in the field along with all the foundational information you'll need. It provides in-depth coverage of a wide range of autoimmune disorders and detailed analyses of suffix trees, plus late-breaking advances regarding biochips and genomes. Featuring helpful gene-finding algorithms, Bioinformatics offers key information on sequence alignment, HMMs, HMM applications, protein secondary structure, microarray techniques, and drug discovery and development. Helpful diagrams accompany mathematical equations throughout, and exercises appear at the end of each chapter to facilitate self-evaluation. This thorough, up-to-date resource features: Worked-out problems illustrating concepts and models End-of-chapter exercises for self-evaluation Material based on student feedback Illustrations that clarify difficult math problems A list of bioinformatics-related websites Bioinformatics covers: Sequence representation and alignment Hidden Markov models Applications of HMMs Gene finding Protein secondary structure prediction Microarray techniques Drug discovery and development Internet resources and public domain databases Contents......Page 7 Preface......Page 13 Acknowledgments......Page 17 1 Preliminaries......Page 19 1.1.1 Amino Acids and Proteins......Page 20 1.1.2 Structures of Proteins......Page 21 1.1.3 Sequence Distribution of Insulin......Page 24 1.1.4 Bioseparation Techniques......Page 27 1.1.5 Nucleic Acids and Genetic Code......Page 30 1.1.6 Genomes—Diversity, Size, and Structure......Page 38 1.2 Probability and Statistics......Page 41 1.2.1 Three Definitions of Probability......Page 42 1.2.3 Independent Events and Bernoulli’s Theorem......Page 43 1.2.4 Discrete Probability Distributions......Page 44 1.2.5 Continuous Probability Distributions......Page 46 1.2.6 Statistical Inference and Hypothesis Testing......Page 48 1.3 Which Is Larger, 2[sup(n)] or n[sup(2)]?......Page 49 1.4 Big O Notation and Asymptotic Order of Functions......Page 50 Summary......Page 51 References and Sources......Page 52 Exercises......Page 53 Part 1 Sequence Alignment and Representation......Page 57 2.1 Introduction to Pairwise Sequence Alignment......Page 59 2.2 Why Study Sequence Alignment......Page 61 2.3 Alignment Grading Function......Page 65 2.4 Optimal Global Alignment of a Pair of Sequences......Page 69 2.5 Dynamic Programming......Page 73 2.7 Dynamic Arrays and O(N) Space......Page 74 2.8 Subquadratic Algorithms for Longest Common Subsequence Problems......Page 75 2.9 Optimal Local Alignment of a Pair of Sequences......Page 77 2.10 Affine Gap Model......Page 78 2.11 Greedy Algorithms for Pairwise Alignment......Page 81 2.12 Other Alignment Methods......Page 83 2.13 Pam and Blosum Matrices......Page 84 Summary......Page 87 References......Page 88 Exercises......Page 89 3.1 Suffix Trees......Page 103 3.2 Algorithm for Suffix Tree Representation of a Sequence......Page 106 3.3 Streaming a Sequence Against a Suffix Tree......Page 107 3.4 String Algorithms......Page 109 3.5 Suffix Trees in String Algorithms......Page 115 3.6 Look-up Tables......Page 117 Summary......Page 118 References......Page 119 Exercises......Page 120 4.1 What Is Multiple-Sequence Alignment?......Page 133 4.3 Optimal MSA by Dynamic Programming......Page 135 4.5 What Are NP Complete Problems?......Page 136 4.6 Center-Star-Alignment Algorithm [4]......Page 137 4.7 Progressive Alignment Methods......Page 139 4.8 The Consensus Sequence......Page 140 4.10 Geometry of Multiple Sequences......Page 141 References......Page 143 Exercises......Page 144 Part 2 Probability Models......Page 149 5.1 Introduction......Page 151 5.2 kth-order Markov Chain......Page 152 5.3 DNA Sequence and Geometric Distribution [2–4]......Page 153 5.4 Three Questions in the HMM......Page 161 5.6 Decoding Problem and Viterbi Algorithm......Page 164 5.7 Relative Entropy......Page 165 5.8 Probabilistic Approach to Phylogeny......Page 167 5.9 Sequence Alignment Using HMMs......Page 170 5.10 Protein Families......Page 171 5.11 Wheel HMMs to Model Periodicity in DNA......Page 174 5.12 Generalized HMM (GHMM)......Page 175 5.14 Multiple Alignments......Page 178 5.15 Classification Using HMMs......Page 179 5.16 Signal Peptide and Signal Anchor Prediction by HMMs......Page 180 5.17 Markov Model and Chargaff's Parity Rules......Page 181 Summary......Page 182 References......Page 183 Exercises......Page 184 6.1 Introduction......Page 197 6.2 Relative Entropy Site-Selection Problem......Page 198 6.3 Maximum-Subsequence Problem......Page 200 6.4 Interpolated Markov Model (IMM)......Page 202 6.5 Shine Dalgarno SD Sites Finding......Page 203 6.6 Gene Annotation Methods......Page 205 6.7 Secondary Structures of Proteins......Page 209 Summary......Page 221 References......Page 222 Exercises......Page 224 Part 3 Measurement Techniques......Page 229 7.1 Introduction......Page 231 7.2 Microarray Detection......Page 241 7.3 Microarray Surfaces......Page 245 7.4 Phosphoramadite Synthesis......Page 249 7.5 Microarray Manufacture......Page 251 7.6 Normalization for cDNA Microarray Data......Page 254 Summary......Page 258 References......Page 259 Exercises......Page 260 8.1 Role of Electrophoresis in the Measurement of Sequence Distribution......Page 263 8.2 Fick’s Laws of Molecular Diffusion......Page 264 8.3 Generalized Fick’s Law of Diffusion......Page 267 8.4 Electrophoresis Apparatus......Page 287 8.5 Electrophoretic Term, Ballistic Term, and Fick Term in the Governing Equation......Page 288 Summary......Page 292 References......Page 293 Exercises......Page 294 A: Internet Hotlinks to Public-Domain Databases......Page 305 B: PERL for Bioinformaticists......Page 317 A......Page 321 B......Page 322 C......Page 323 D......Page 324 F......Page 325 G......Page 326 H......Page 327 J......Page 328 L......Page 329 M......Page 330 N......Page 331 P......Page 332 R......Page 334 S......Page 335 T......Page 337 Z......Page 338 Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. GET FULLY UP-TO-DATE ON BIOINFORMATICS-THE TECHNOLOGY OF THE 21ST CENTURY Bioinformatics showcases the latest developments in the field along with all the foundational information you'll need. It provides in-depth coverage of a wide range of autoimmune disorders and detailed analyses of suffix trees, plus late-breaking advances regarding biochips and genomes. Featuring helpful gene-finding algorithms, Bioinformatics offers key information on sequence alignment, HMMs, HMM applications, protein secondary structure, microarray techniques, and drug discovery and development. Helpful diagrams accompany mathematical equations throughout, and exercises appear at the end of each chapter to facilitate self-evaluation. This thorough, up-to-date resource features: Bioinformatics covers: "A state-of-the-art textbook on bioinformatics covering the latest 21st-century technology. An essential tool, this book explores the cutting-edge methods of bioinformatics, presenting a wide range of diagrams, mathematical equations, worked examples, and exercises to illustrate the concepts and models. Bioinformatics discusses auto-immune disorders and enumerates the motivation for sequence alignment. The text provides gene-finding algorithms and introduces binomial heap for the maximum increasing subsequence problem. There is also a wealth of information on suffix trees ... HMM ... HMM applications ... protein secondary structure ... microarray techniques ... drug discovery and development ... and advances in biochip and genome completions and sequence alignment. In addition, this valuable resource includes a listing of Internet sites in bioinformatics, which contain constantly updated information on this fast-changing field." "Bioinformatics offers in-depth coverage of a wide range of autoimmune disorders, detailed analyses of suffix trees, and the latest biochip and genome advances." "Featuring helpful gene-finding algorithms, Bioinformatics offers key information on sequence alignment, HMMs, HMM applications, protein secondary structure, microarray techniques, and drug discovery and development. Diagrams accompany mathematical equations throughout, and exercises appear at the end of each chapter to facilitate self-evaluation."--Jacket Preliminaries Alignment of a pair of sequences Sequence representation and string algorithms Multiple sequence alignment Hidden Markov model, HMM, and applications Gene finding, protein secondary structure Biochips Electrophoretic techniques and finite speed diffusion.