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Multiple Sequence Alignment Methods

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Cover of 'Multiple Sequence Alignment Methods'

Table of Contents

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    Book Overview
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    Chapter 1 Dynamic Programming
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    Chapter 2 Heuristic Alignment Methods
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    Chapter 3 Objective Functions
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    Chapter 4 Who watches the watchmen? An appraisal of benchmarks for multiple sequence alignment.
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    Chapter 5 BLAST and FASTA Similarity Searching for Multiple Sequence Alignment
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    Chapter 6 Multiple Sequence Alignment Methods
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    Chapter 7 T-coffee: tree-based consistency objective function for alignment evaluation.
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    Chapter 8 MAFFT: Iterative Refinement and Additional Methods
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    Chapter 9 Multiple Sequence Alignment Methods
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    Chapter 10 Phylogeny-aware alignment with PRANK.
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    Chapter 11 GramAlign: Fast alignment driven by grammar-based phylogeny
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    Chapter 12 Multiple Sequence Alignment with DIALIGN
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    Chapter 13 PicXAA: A Probabilistic Scheme for Finding the Maximum Expected Accuracy Alignment of Multiple Biological Sequences
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    Chapter 14 Multiple Protein Sequence Alignment with MSAProbs
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    Chapter 15 Large-Scale Multiple Sequence Alignment and Tree Estimation Using SATé
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    Chapter 16 PRALINE: A Versatile Multiple Sequence Alignment Toolkit
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    Chapter 17 PROMALS3D: Multiple Protein Sequence Alignment Enhanced with Evolutionary and Three-Dimensional Structural Information
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    Chapter 18 MSACompro: Improving Multiple Protein Sequence Alignment by Predicted Structural Features
Attention for Chapter 1: Dynamic Programming
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Chapter title
Dynamic Programming
Chapter number 1
Book title
Multiple Sequence Alignment Methods
Published in
Methods in molecular biology, August 2013
DOI 10.1007/978-1-62703-646-7_1
Pubmed ID
Book ISBNs
978-1-62703-645-0, 978-1-62703-646-7
Authors

Ö. Ufuk Nalbantoğlu, Nalbantoğlu, Ö. Ufuk

Editors

David J Russell

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 114 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
Switzerland 1 <1%
Pakistan 1 <1%
Brazil 1 <1%
Slovakia 1 <1%
Chile 1 <1%
Korea, Republic of 1 <1%
China 1 <1%
Greece 1 <1%
Other 1 <1%
Unknown 102 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 44 39%
Student > Master 24 21%
Researcher 11 10%
Student > Bachelor 8 7%
Student > Doctoral Student 6 5%
Other 14 12%
Unknown 7 6%
Readers by discipline Count As %
Computer Science 27 24%
Engineering 22 19%
Agricultural and Biological Sciences 19 17%
Economics, Econometrics and Finance 8 7%
Mathematics 7 6%
Other 20 18%
Unknown 11 10%