Ultrafast Genomic Database Search using Layered Locality Sensitive Hashing
| Autor: | Sanghamitra Bandyopadhyay, Angana Chakraborty |
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| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Clustering high-dimensional data Computer science business.industry Nearest neighbor search Approximation algorithm Genomics Pattern recognition Repetitive Regions Genomic databases Locality-sensitive hashing 03 medical and health sciences ComputingMethodologies_PATTERNRECOGNITION 030104 developmental biology Artificial intelligence Cluster analysis business |
| Zdroj: | 2018 Fifth International Conference on Emerging Applications of Information Technology (EAIT). |
| Popis: | In this article, we will demonstrate Layered Locality Sensitive Hashing in genomic sequence comparison. Locality Sensitive Hashing based algorithms have already been proved to be successful for approximate nearest neighbor search in high dimensional data. Genomic database search is the primary task for homology detection and motif identification. However, the huge genome size and unknown repetitive regions make the task even more difficult. To tackle this problem we have introduced layered locality sensitive hashing for large scale genomic comparisons. As it turns out, the proposed method reduces the search time by 93.6%, while producing results almost as good as the exact ones. |
| Databáze: | OpenAIRE |
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