Abstract | ||
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Comparing genomes to identify polymorphisms is a difficult task, especially beyond single nucleotide poly-morphisms. Polymorphism detection is important in disease association studies as well as in phylogenetic tree reconstruc-tion. We present a method for identifying polymorphisms in genomes by using a modified version de Bruijn graphs, data structures widely used in genome assembly from Next-Generation Sequencing. Using our method, we are able to identify polymorphisms that exist within a genome as well as well as see graph structures that form in the de Bruijn graph for particular types of polymorphisms (translocations, etc.) |
Year | DOI | Venue |
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2017 | 10.1109/BIBE.2017.00-53 | 2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) |
Keywords | Field | DocType |
de Bruijn graph,graph,GWAS,phylogenetics,polymorphism | Genome,Phylogenetic tree,Computer science,Genome-wide association study,Genomics,De Bruijn graph,Artificial intelligence,Computational biology,De Bruijn sequence,Phylogenetics,Machine learning,Sequence assembly | Conference |
ISSN | ISBN | Citations |
2471-7819 | 978-1-5386-1325-2 | 0 |
PageRank | References | Authors |
0.34 | 0 | 8 |
Name | Order | Citations | PageRank |
---|---|---|---|
Stanley Fujimoto | 1 | 13 | 4.27 |
Cole A. Lyman | 2 | 0 | 1.35 |
Anton Suvorov | 3 | 0 | 1.35 |
Paul Bodily | 4 | 15 | 4.32 |
Quinn Snell | 5 | 390 | 51.47 |
Keith Crandall | 6 | 97 | 14.34 |
Seth M. Bybee | 7 | 4 | 1.69 |
Mark J. Clement | 8 | 384 | 46.31 |