Efficient similarity search in large databases of tree structured objects

2004 ◽  
Author(s):  
K. Kailing ◽  
H.-P. Kriegel ◽  
S. Schonauer ◽  
T. Seidl
Keyword(s):  
Similarity Search ◽  
Large Databases ◽  
Structured Objects

scholarly journals RAFTS3: Rapid Alignment-Free Tool for Sequence Similarity Search

2016 ◽  
Author(s):  
Ricardo Assunção Vialle ◽  
Fábio de Oliveira Pedrosa ◽  
Vinicius Almir Weiss ◽  
Dieval Guizelini ◽  
Juliana Helena Tibaes ◽  
...  
Keyword(s):  
Similarity Search ◽  
Sequence Similarity ◽  
Biological Data ◽  
Amino Acid Residues ◽  
Binary Matrix ◽  
Protein Databases ◽  
Alignment Free ◽  
Large Databases ◽  
Search Tool ◽  
Time Required

AbstractBackgroundSimilarity search of a given protein sequence against a database is an essential task in genome analysis. Sequence alignment is the most used method to perform such analysis. Although this approach is efficient, the time required to perform searches against large databases is always a challenge. Alignment-free techniques offer alternatives to comparing sequences without the need of alignment.ResultsHere We developed RAFTS3, a fast protein similarity search tool that utilizes a filter step for candidate selection based on shared k-mers and a comparison measure using a binary matrix of co-occurrence of amino acid residues. RAFTS3performed searches many times faster than those with BLASTp against large protein databases, such as NR, Pfam or UniRef, with a small loss of sensitivity depending on the similarity degree of the sequences.ConclusionsRAFTS3 is a new alternative for fast comparison of proteinsequences genome annotation and biological data mining. The source code and the standalone files for Windows and Linux platform are available at: https://sourceforge.net/projects/rafts3/

scholarly journals Molecular-level similarity search brings computing to DNA data storage

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Callista Bee ◽  
Yuan-Jyue Chen ◽  
Melissa Queen ◽  
David Ward ◽  
Xiaomeng Liu ◽  
...  
Keyword(s):  
Data Storage ◽  
Similarity Search ◽  
Molecular Mechanisms ◽  
Error Correcting Codes ◽  
Synthetic Dna ◽  
Digital Storage ◽  
Hybridization Probes ◽  
Large Databases ◽  
Similar Images ◽  
Storage Technologies

AbstractAs global demand for digital storage capacity grows, storage technologies based on synthetic DNA have emerged as a dense and durable alternative to traditional media. Existing approaches leverage robust error correcting codes and precise molecular mechanisms to reliably retrieve specific files from large databases. Typically, files are retrieved using a pre-specified key, analogous to a filename. However, these approaches lack the ability to perform more complex computations over the stored data, such as similarity search: e.g., finding images that look similar to an image of interest without prior knowledge of their file names. Here we demonstrate a technique for executing similarity search over a DNA-based database of 1.6 million images. Queries are implemented as hybridization probes, and a key step in our approach was to learn an image-to-sequence encoding ensuring that queries preferentially bind to targets representing visually similar images. Experimental results show that our molecular implementation performs comparably to state-of-the-art in silico algorithms for similarity search.

Converging Evidence for Developmental Trauma Disorder: Empirical Support From Large Databases

2008 ◽  
Author(s):  
Bradley C. Stolbach ◽  
Frank Putnam ◽  
Melissa Perry ◽  
Karen Putnam ◽  
William Harris ◽  
...  
Keyword(s):  
Empirical Support ◽  
Developmental Trauma ◽  
Developmental Trauma Disorder ◽  
Large Databases
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