Sequence Alignment: Methods, Models, Concepts, and Strategies / Edition 1

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Overview


The sequencing of the human genome involved thousands of scientists but used relatively few tools. Today, obtaining sequences is simpler, but aligning the sequences—making sure that sequences from one source are properly compared to those from other sources—remains a complicated but underappreciated aspect of comparative molecular biology. This volume, the first to focus on this crucial step in analyzing sequence data, is about the practice of alignment, the procedures by which alignments are established, and more importantly, how the outcomes of any alignment algorithm should be interpreted. Edited by Michael S. Rosenberg with essays by many of the field's leading experts, Sequence Alignment covers molecular causes, computational advances, approaches for assessing alignment quality, and philosophical underpinnings of the algorithms themselves.
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Product Details

  • ISBN-13: 9780520256972
  • Publisher: University of California Press
  • Publication date: 3/11/2009
  • Edition number: 1
  • Pages: 360
  • Product dimensions: 5.90 (w) x 9.10 (h) x 1.10 (d)

Meet the Author


Michael S. Rosenberg is Associate Professor of Computational Evolutionary Biology and Bioinformatics in the School of Life Sciences and the Center for Evolutionary Functional Genomics of the Biodesign Institute at Arizona State University.
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Table of Contents


Contributors
Preface
1. Sequence Alignment: Concepts and History
2. Insertion and Deletion Events, Their Molecular Mechanisms, and Their Impact on Sequence Alignments
3. Local versus Global Alignments
4. Computing Multiple Sequence Alignment with Template-Based Methods
5. Sequence Evolution Models for Simultaneous Alignment and Phylogeny Reconstruction
6. Phylogenetic Hypotheses and the Utility of Multiple Sequence Alignment
7. Structural and Evolutionary Considerations for Multiple Sequence Alignment of RNA, and the Challenges for Algorithms That Ignore Them
8. Constructing Alignment Benchmarks
9. Simulation Approaches to Evaluating Alignment Error and Methods for Comparing Alternate Alignments
Contents
10. Robust Inferences from Ambiguous Alignments
11. Strategies for Efficient Exploitation of the Informational Content of Protein Multiple Alignments
References
Index
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