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Bioinformatics

Overview of attention for book
Attention for Chapter 8: Multiple Sequence Alignment.
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Chapter title
Multiple Sequence Alignment.
Chapter number 8
Book title
Bioinformatics
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6622-6_8
Pubmed ID
Book ISBNs
978-1-4939-6620-2, 978-1-4939-6622-6
Authors

Punto Bawono, Maurits Dijkstra, Walter Pirovano, Anton Feenstra, Sanne Abeln, Jaap Heringa, Bawono, Punto, Dijkstra, Maurits, Pirovano, Walter, Feenstra, Anton, Abeln, Sanne, Heringa, Jaap

Editors

Jonathan M. Keith

Abstract

The increasing importance of Next Generation Sequencing (NGS) techniques has highlighted the key role of multiple sequence alignment (MSA) in comparative structure and function analysis of biological sequences. MSA often leads to fundamental biological insight into sequence-structure-function relationships of nucleotide or protein sequence families. Significant advances have been achieved in this field, and many useful tools have been developed for constructing alignments, although many biological and methodological issues are still open. This chapter first provides some background information and considerations associated with MSA techniques, concentrating on the alignment of protein sequences. Then, a practical overview of currently available methods and a description of their specific advantages and limitations are given, to serve as a helpful guide or starting point for researchers who aim to construct a reliable MSA.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 201 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
France 1 <1%
New Zealand 1 <1%
Brazil 1 <1%
Spain 1 <1%
Iran, Islamic Republic of 1 <1%
Unknown 194 97%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 42 21%
Student > Ph. D. Student 25 12%
Researcher 25 12%
Student > Master 25 12%
Other 7 3%
Other 26 13%
Unknown 51 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 50 25%
Agricultural and Biological Sciences 46 23%
Computer Science 16 8%
Immunology and Microbiology 7 3%
Pharmacology, Toxicology and Pharmaceutical Science 7 3%
Other 21 10%
Unknown 54 27%