Recursive Lists of Clusters: A Dynamic Data Structure for Range Queries in Metric Spaces

2005 ◽  
pp. 843-853 ◽  
Author(s):  
Margarida Mamede
Keyword(s):  
Data Structure ◽  
Metric Spaces ◽  
Range Queries ◽  
Dynamic Data ◽  
Dynamic Data Structure

scholarly journals An Optimal Dynamic Data Structure for Stabbing-Semigroup Queries

2012 ◽  
Vol 41 (1) ◽  
pp. 104-127 ◽  
Author(s):  
Pankaj K. Agarwal ◽  
Lars Arge ◽  
Haim Kaplan ◽  
Eyal Molad ◽  
Robert E. Tarjan ◽  
...  
Keyword(s):  
Data Structure ◽  
Dynamic Data ◽  
Optimal Dynamic ◽  
Dynamic Data Structure

scholarly journals A dynamic data structure for flexible molecular maintenance and informatics

2010 ◽  
Vol 27 (1) ◽  
pp. 55-62 ◽  
Author(s):  
C. Bajaj ◽  
R. A. Chowdhury ◽  
M. Rasheed
Keyword(s):  
Data Structure ◽  
Dynamic Data ◽  
Dynamic Data Structure

scholarly journals Metannot: A succinct data structure for compression of colors in dynamic de Bruijn graphs

2017 ◽  
Author(s):  
Harun Mustafa ◽  
André Kahles ◽  
Mikhail Karasikov ◽  
Gunnar Rätsch
Keyword(s):  
Data Structure ◽  
High Throughput Sequencing ◽  
Sequence Data ◽  
Data Sets ◽  
Sequencing Data ◽  
Dynamic Data ◽  
De Bruijn Graphs ◽  
Dna And Rna ◽  
Succinct Data Structure ◽  
Dynamic Data Structure

AbstractMuch of the DNA and RNA sequencing data available is in the form of high-throughput sequencing (HTS) reads and is currently unindexed by established sequence search databases. Recent succinct data structures for indexing both reference sequences and HTS data, along with associated metadata, have been based on either hashing or graph models, but many of these structures are static in nature, and thus, not well-suited as backends for dynamic databases.We propose a parallel construction method for and novel application of the wavelet trie as a dynamic data structure for compressing and indexing graph metadata. By developing an algorithm for merging wavelet tries, we are able to construct large tries in parallel by merging smaller tries constructed concurrently from batches of data.When compared against general compression algorithms and those developed specifically for graph colors (VARI and Rainbowfish), our method achieves compression ratios superior to gzip and VARI, converging to compression ratios of 6.5% to 2% on data sets constructed from over 600 virus genomes.While marginally worse than compression by bzip2 or Rainbowfish, this structure allows for both fast extension and query. We also found that additionally encoding graph topology metadata improved compression ratios, particularly on data sets consisting of several mutually-exclusive reference genomes.It was also observed that the compression ratio of wavelet tries grew sublinearly with the density of the annotation matrices.This work is a significant step towards implementing a dynamic data structure for indexing large annotated sequence data sets that supports fast query and update operations. At the time of writing, no established standard tool has filled this niche.

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