Abstract
Using a probabilistic data structure to store DNA assembly graphs results in a significant memory savings over other methods. As long as the Bloom filter remains below a specific false positive rate, it remains possible to traverse the graph. Using a Bloom filter has many applications in metagenomics, mRNAseq, read filtering, and error correction. We are currently exploring these possibilities and more.
Original language | English (US) |
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Title of host publication | 2012 IEEE 2nd International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2012 |
DOIs | |
State | Published - May 8 2012 |
Externally published | Yes |
Event | 2012 IEEE 2nd International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2012 - Las Vegas, NV, United States Duration: Feb 23 2012 → Feb 25 2012 |
Other
Other | 2012 IEEE 2nd International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2012 |
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Country | United States |
City | Las Vegas, NV |
Period | 2/23/12 → 2/25/12 |
Keywords
- Bloom filters
- de Bruijn graphs
- k-mers
- metagenomics
- next-generation sequencing
ASJC Scopus subject areas
- Biomedical Engineering
- Applied Mathematics