Biological Sequence Analysis Using the SeqAn C++ Library

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A01=Andreas Gogol-Doring
A01=Knut Reinert
algorithm
algorithm benchmarking
Algorithm Engineering
Aligning sequences with LAGAN
alignment
Alignment Graphs
array
Author_Andreas Gogol-Doring
Author_Knut Reinert
Basic statistical indices for SeqAn
Biological Sequence Analysis
Biological Sequences
C++ bioinformatics
Category=PS
Category=UMB
Category=UY
computational genomics
data
Edit Distance
efficient biological data analysis
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
genome assembly methods
Global Alignment
Graph Data Structures
graphs
Int
Local Alignment
Locality Sensitive Hashing
Memory Block
motif discovery
Multiple alignment with segments
Needleman Wunsch Algorithm
needlemanwunsch
Optimal Alignment
Programming techniques
Running Time
Sequence Analysis
sequence pattern matching
Sequences A1
Software Libraries
Standard Template Library
String Indices
String Sets
structure
suffix
Suffix Arrays
Suffix Trees
Template Argument
The design in examples
unsigned
Unsigned Int
Vice Versa

Product details

  • ISBN 9781420076233
  • Weight: 590g
  • Dimensions: 156 x 234mm
  • Publication Date: 11 Nov 2009
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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An Easy-to-Use Research Tool for Algorithm Testing and Development

Before the SeqAn project, there was clearly a lack of available implementations in sequence analysis, even for standard tasks. Implementations of needed algorithmic components were either unavailable or hard to access in third-party monolithic software products. Addressing these concerns, the developers of SeqAn created a comprehensive, easy-to-use, open source C++ library of efficient algorithms and data structures for the analysis of biological sequences. Written by the founders of this project, Biological Sequence Analysis Using the SeqAn C++ Library covers the SeqAn library, its documentation, and the supporting infrastructure.

The first part of the book describes the general library design. It introduces biological sequence analysis problems, discusses the benefit of using software libraries, summarizes the design principles and goals of SeqAn, details the main programming techniques used in SeqAn, and demonstrates the application of these techniques in various examples. Focusing on the components provided by SeqAn, the second part explores basic functionality, sequence data structures, alignments, pattern and motif searching, string indices, and graphs. The last part illustrates applications of SeqAn to genome alignment, consensus sequence in assembly projects, suffix array construction, and more.

This handy book describes a user-friendly library of efficient data types and algorithms for sequence analysis in computational biology. SeqAn enables not only the implementation of new algorithms, but also the sound analysis and comparison of existing algorithms.

Visit SeqAn for more information.

Co-founder of the SeqAn project, Andreas Gogol-Döring works at the Max Delbrück Center for Molecular Medicine in Berlin, Germany. He was previously a research associate in the Algorithmic Bioinformatics group in the Department of Computer Science at Freie Universität Berlin in Germany.

Co-founder of the SeqAn project, Knut Reinert is a professor and head of the Algorithmic Bioinformatics group in the Department of Computer Science at Freie Universität Berlin in Germany.

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