ALGORITHMS IN BIO INFORMATICS. Chapman & Hall/CRC Mathematical and Computational Biology Series A PRACTICAL INTRODUCTION. CRC Press WING-KIN SUNG

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1 Chapman & Hall/CRC Mathematical and Computational Biology Series ALGORITHMS IN BIO INFORMATICS A PRACTICAL INTRODUCTION WING-KIN SUNG CRC Press Taylor & Francis Group Boca Raton London New York CRC Press is an imprint of the Taylor & Francis Croup an informa business A CHAPMAN & HALL BOOK

2 Contents Preface xv 1 Introduction to Molecular Biology 1 11 DNA, RNA, and Protein Proteins DNA RNA 9 12 Genome, Chromosome, and Gene Genome Chromosome Gene Complexity of the Organism versus Genome Size Number of Genes versus Genome Size Replication and Mutation of DNA Central Dogma (from DNA to Protein) Transcription (Prokaryotes) Transcription (Eukaryotes) Translation Post-Translation Modification (PTM) Population Genetics Basic Biotechnological Tools Restriction Enzymes Sonication Cloning PCR Gel Electrophoresis Hybridization Next Generation DNA Sequencing Brief History of Bioinformatics Exercises 27 2 Sequence Similarity Introduction Global Alignment Problem Needleman-Wunsch Algorithm Running Time Issue Space Efficiency Issue 35 vii

3 viii 224 More on Global Alignment Local Alignment Semi-Global Alignment Gap Penalty General Gap Penalty Model Affine Gap Penalty Model Convex Gap Model Scoring Function Scoring Function for DNA Scoring Function for Protein Exercises 53 3 Suffix Tree Introduction Suffix Tree Simple Applications of a Suffix Tree Exact String Matching Problem Longest Repeated Substring Problem Longest Common Substring Problem Longest Common Prefix (LCP) Finding a Palindrome Extracting the Embedded Suffix Tree of a String from the Generalized Suffix Tree Common Substring of 2 or More Strings Construction of a Suffix Tree Step 1: Construct the Odd Suffix Tree Step 2: Construct the Even Suffix Tree Step 3: Merge the Odd and the Even Suffix Trees Suffix Array Construction of a Suffix Array Exact String Matching Using a Suffix Array FM-Index Definition The occ Data Structure Exact String Matching Using the FM-Index Approximate Searching Problem Exercises Genome Alignment Introduction Maximum Unique Match (MUM) How to Find MUMs MUMmerl: LCS Dynamic Programming Algorithm in 0(n2) Time 432 An 0(n logn)-time Algorithm 93

4 ix 44 MUMmer2 and MUMmer Reducing Memory Usage Employing a New Alternative Algorithm for Finding MUMs Clustering Matches Extension of the Definition of MUM Mutation Sensitive Alignment Concepts and Definitions The Idea of the Heuristic Algorithm Experimental Results Dot Plot for Visualizing the Alignment Further Reading Exercises Database Search Introduction Biological Database Database Searching Types of Algorithms Smith-Waterman Algorithm Ill 53 FastA Ill 531 FastP Algorithm FastA Algorithm BLAST BLAST BLAST BLAST1 versus BLAST BLAST versus FastA Statistics for Local Alignment Variations of the BLAST Algorithm MegaBLAST BLAT PatternHunter PSI-BLAST (Position-Specific Iterated BLAST) 56 Q-gram Alignment based on Suffix ARrays 123 (QUASAR) Algorithm Speeding Up and Reducing the Space for QUASAR Time Analysis Locality-Sensitive Hashing BWT-SW Aligning Query Sequence to Suffix Tree Meaningful Alignment Are Existing Database Searching Methods Sensitive Enough? Exercises 136

5 X 6 Multiple Sequence Alignment Introduction Formal Definition of the Multiple Sequence Alignment Prob lem Methods for Solving the MSA Problem Dynamic Programming Method Center Star Method Progressive Alignment Method ClustalW Profile-Profile Alignment Limitation of Progressive Alignment Construction Iterative Method MUSCLE Log-Expectation (LE) Score Further Reading Exercises Phylogeny Reconstruction Introduction Mitochondrial DNA and Inheritance The Constant Molecular Clock Phylogeny Applications of Phylogeny Phylogenetic Tree Reconstruction Character-Based Phylogeny Reconstruction Algorithm Maximum Parsimony Compatibility Maximum Likelihood Problem Distance-Based Phylogeny Reconstruction Algorithm Additive Metric and Ultrametric Unweighted Pair Group Method with Arithmetic Mean (UPGMA) Additive Tree Reconstruction Nearly Additive Tree Reconstruction Can We Apply Distance-Based Methods Given a Character-State Matrix? Bootstrapping Can Tree Reconstruction Methods Infer the Correct Tree? Exercises Phylogeny Comparison Introduction Similarity Measurement Computing MAST by Dynamic Programming MAST for Unrooted Trees 202

6 xi 83 Dissimilarity Measurements Robinson-Foulds Distance Nearest Neighbor Interchange Distance (NNI) Subtree Transfer Distance (STT) Quartet Distance Consensus Tree Problem Strict Consensus Tree Majority Rule Consensus Tree Median Consensus Tree Greedy Consensus Tree R* Tree Further Reading Exercises Genome Rearrangement Introduction Types of Genome Rearrangements Computational Problems Sorting an Unsigned Permutation by Reversals Upper and Lower Bound on an Unsigned Reversal Dis tance Approximation Algorithm for Sorting an Unsigned Permutation Approximation Algorithm for Sorting an Unsigned Permutation Sorting a Signed Permutation by Reversals Upper Bound on Signed Reversal Distance Elementary Intervals, Cycles, and Components The Hannenhalli-Pevzner Theorem Further Reading Exercises Motif Finding Introduction Identifying Binding Regions of TFs Motif Model The Motif Finding Problem Scanning for Known Motifs Statistical Approaches Gibbs Motif Sampler MEME Combinatorial Approaches Exhaustive Pattern-Driven Algorithm Sample-Driven Approach Suffix Tree-Based Algorithm 263

7 xii 1074 Graph-Based Method Scoring Function Motif Ensemble Methods 267 I 091 Approach of MotifVoter Motif Filtering by the Discriminative and Consensus Criteria Sites Extraction and Motif Generation Can Motif Finders Discover the Correct Motifs? Motif Finding Utilizing Additional Information Regulatory Element Detection Using Correlation with Expression Discovery of Regulatory Elements by Phylogenetic Footprinting Exercises RNA Secondary Structure Prediction Introduction 281 II 11 Base Interactions in RNA RNA Structures Obtaining RNA Secondary Structure Experimentally 113 RNA Structure Prediction Based on Sequence Only Structure Prediction with the Assumption That There is No Pseudoknot Nussinov Folding Algorithm ZUKER Algorithm Time Analysis Speeding up Multi-Loops Speeding up Internal Loops Structure Prediction with Pseudoknots Definition of a Simple Pseudoknot Akutsu's Algorithm for Predicting an RNA Secondary Structure with Simple Pseudoknots Exercises Peptide Sequencing Introduction Obtaining the Mass Spectrum of a Peptide Modeling the Mass Spectrum of a Fragmented Peptide Amino Acid Residue Mass Fragment Ion Mass De Novo Peptide Sequencing Using Dynamic Programming Scoring by Considering y-ions Scoring by Considering y-ions and b-ions De Novo Sequencing Using Graph-Based Approach Peptide Sequencing via Database Search 319

8 xiii 127 Further Reading Exercises Population Genetics Introduction Locus, Genotype, Allele, and SNP Genotype Frequency and Allele Frequency Haplotype and Phenotype Technologies for Studying the Human Population Bioinformatics Problems Hardy-Weinberg Equilibrium Linkage Disequilibrium D and D' r Genotype Phasing Clark's Algorithm Perfect Phylogeny Haplotyping Problem Maximum Likelihood Approach Phase Algorithm Tag SNP Selection Zhang et al's Algorithm IdSelect Association Study Categorical Data Analysis Relative Risk and Odds Ratio Linear Regression Logistic Regression Exercises 344 References 349 Index 375