Efficient Querying on Gnomic Databases by Using Metric Space Indexing Techniques
نویسندگان
چکیده
A genomic database consists of a set of nucleotide sequences, for which an important kind of queries is the local sequence alignment. This paper investigates two different indexing techniques, namely the variations of GNAT trees [1] and M-trees [3], to support fast query evaluation for local alignment, by transforming the alignment problem to a variant metric space neighborhood search problem.
منابع مشابه
Efficient Querying on Genomic Databases by Using Metric Space Indexing Techniques
A genomic database consists of a set of nucleotide sequences, for which an important kind of queries is the local sequence alignment. This paper investigates two different indexing techniques, namely the variations of GNAT trees [1] and M-trees [3], to support fast query evaluation for local alignment, by transforming the alignment problem to a variant metric space neighborhood search problem.
متن کاملUniversal Indexing of Arbitrary Similarity Models
The increasing amount of available unstructured content together with the growing number of large non-relational databases put more emphasis on the content-based retrieval and precisely on the area of similarity searching. Although there exist several indexing methods for efficient querying, not all of them are best-suited for arbitrary similarity models. Having a metric space, we can easily ap...
متن کاملEfficient Querying on Genomic Databases by Using Metric Space Indexing Technology
The " Arbeitspapiere der GMD – GMD Technical Reports " primarily comprise preliminary publications , specific partial results and complementary material. In the interest of a subsequent final publication the " Arbeitspapiere/Technical Reports " should not be copied. Critical comments would be appreciated by the authors. No part of this publication may be reproduced or further processed in any f...
متن کاملQuerying Mobile Objects in Spatio-Temporal Databases
In dynamic spatio-temporal environments where objects may continuously move in space, maintaining consistent information about the location of objects and processing motion-specific queries is a challenging problem. In this paper, we focus on indexing and query processing techniques for mobile objects. Specifically, we develop a classification of different types of selection queries that arise ...
متن کاملOptimal Embedding for Shape Indexing in Medical Image Databases
Fast retrieval using organ shapes is crucial in medical image databases since shape is a clinically prominent feature. In this paper, we propose that 2-D shapes in medical image databases can be indexed by embedding them into a vector space and using efficient vector space indexing. An optimal shape space embedding is proposed for this purpose. Experimental results of indexing vertebral shapes ...
متن کامل