Name
Abstract | ||
|---|---|---|
String barcoding is a recently introduced technique for genomic based identification of microorganisms. In this paper, we describe the engineering of highly scalable algorithms for robust string barcoding. Our methods enable distinguisher selection based on whole genomic sequences of hundreds of microorganisms of up to bacterial size, on a well equipped workstation. Experimental results on both randomly generated and NCBI genomic data show that whole-genome based selection results in a number of distinguishers nearly matching the information theoretic lower bounds for the problem. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1504/IJBRA.2005.007574 | International journal of bioinformatics research and applications |
Keywords | DocType | Volume |
bacterial size genomes,information theoretic lower bound,scalable algorithm,string barcoding,selection result,greedy algorithm.,whole genomic sequence,distinguisher selection,setcover problem,robust string barcoding,ncbi genomic data,bacterial size,applicability range | Conference | 1 |
Issue | ISSN | ISBN |
2 | 1744-5485 | 3-540-26043-9 |
Citations | PageRank | References |
9 | 1.05 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bhaskar DasGupta | 1 | 551 | 70.14 |
| Kishori M. Konwar | 2 | 107 | 17.49 |
| Ion I. Mandoiu | 3 | 372 | 47.28 |
| Alex A. Shvartsman | 4 | 266 | 20.83 |