Title |
Genome alignment with graph data structures: a comparison
|
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Published in |
BMC Bioinformatics, April 2014
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DOI | 10.1186/1471-2105-15-99 |
Pubmed ID | |
Authors |
Birte Kehr, Kathrin Trappe, Manuel Holtgrewe, Knut Reinert |
Abstract |
Recent advances in rapid, low-cost sequencing have opened up the opportunity to study complete genome sequences. The computational approach of multiple genome alignment allows investigation of evolutionarily related genomes in an integrated fashion, providing a basis for downstream analyses such as rearrangement studies and phylogenetic inference.Graphs have proven to be a powerful tool for coping with the complexity of genome-scale sequence alignments. The potential of graphs to intuitively represent all aspects of genome alignments led to the development of graph-based approaches for genome alignment. These approaches construct a graph from a set of local alignments, and derive a genome alignment through identification and removal of graph substructures that indicate errors in the alignment. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 9 | 21% |
United States | 8 | 19% |
Japan | 2 | 5% |
Germany | 2 | 5% |
Norway | 2 | 5% |
Canada | 2 | 5% |
Mexico | 1 | 2% |
Spain | 1 | 2% |
India | 1 | 2% |
Other | 3 | 7% |
Unknown | 12 | 28% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 24 | 56% |
Members of the public | 17 | 40% |
Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Unknown | 1 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 8 | 4% |
Germany | 2 | 1% |
United Kingdom | 2 | 1% |
Norway | 1 | <1% |
Australia | 1 | <1% |
Sweden | 1 | <1% |
Colombia | 1 | <1% |
Netherlands | 1 | <1% |
South Africa | 1 | <1% |
Other | 2 | 1% |
Unknown | 173 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 49 | 25% |
Student > Ph. D. Student | 30 | 16% |
Student > Bachelor | 24 | 12% |
Student > Master | 24 | 12% |
Other | 16 | 8% |
Other | 32 | 17% |
Unknown | 18 | 9% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 69 | 36% |
Computer Science | 53 | 27% |
Biochemistry, Genetics and Molecular Biology | 33 | 17% |
Arts and Humanities | 3 | 2% |
Medicine and Dentistry | 3 | 2% |
Other | 11 | 6% |
Unknown | 21 | 11% |