v
Table of Contents
Foreword
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xi
Preface
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xiii
Part I. Introduction
1. Hello BLAST
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3
What Is BLAST? 3
Using NCBI-BLAST 4
Alternate Output Formats 12
Alternate Alignment Views 13
The Next Step 14
Further Reading 15
Part II. Theory
2. Biological Sequences
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
19
The Central Dogma of Molecular Biology 19
Evolution 27
Genomes and Genes 35
Biological Sequences and Similarity 38
Further Reading 39
3. Sequence Alignment
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
40
Global Alignment: Needleman-Wunsch 40
Local Alignment: Smith-Waterman 46
vi | Table of Contents
Dynamic Programming 50
Algorithmic Complexity 50
Global Versus Local 50
Variations 51
Final Thoughts 53
Further Reading 53
4. Sequence Similarity
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
55
Introduction to Information Theory 55
Amino Acid Similarity 57
Scoring Matrices 59
Target Frequencies, lambda, and H 60
Sequence Similarity 64
Karlin-Altschul Statistics 65
Sum Statistics and Sum Scores 67
Further Reading 70
Part III. Practice
5. BLAST
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75
The Five BLAST Programs 75
The BLAST Algorithm 76
Further Reading 87
6. Anatomy of a BLAST Report
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
88
Basic Structure 88
Alignments 90
7. A BLAST Statistics Tutorial
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96
Basic BLAST Statistics 96
Using Statistics to Understand BLAST Results 109
Where Did My Oligo Go? 109
8. 20 Tips to Improve Your BLAST Searches
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116
8.1 Don’t Use the Default Parameters 116
8.2 Treat BLAST Searches as Scientific Experiments 116
8.3 Perform Controls, Especially in the Twilight Zone 117

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