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SETTER

Type: 
Bioinformatics & Cheminformatics
One line description: 
RNA structure similarity search
Annotation: 

SETTER web-server utilizes SETTER (SEcondary sTructure-based TERtiary Structure Similarity Algorithm) method for fast and accurate structural pairwise alignment. The server is capable of comparing a pair of RNA structures or using one strucutre as a query and search against a user-defined database of RNA structures. The efficiency of the algorithm is given by the decomposition of the RNA structure into the set of non-overlapping generalized secondary structure motifs (GSSUs). GSSU usually resembles a hairpin motif possibly containing bulges and/or internal loops in its stem part. A segmentation to GSSUs offers good scalability with respect to the structure size (SETTER scales linearly with the structure size) because the number of residues in GSSUs (SETTER scales quadratically with the GSSU size) generally does not increase with increased size of the RNA structure. The underlying SETTER algorithm is both accurate and very fast, and does not impose limits on the size of aligned RNA structures. SETTER is able to compare a pair of even the largest RNA structure in less than one minute.

Developers: 
david.hoksza

SIR

Type: 
Multimedia
One line description: 
Smart image retrieval
Annotation: 

When determining visual similarity of two images, it is evaluated on feature representations which consist of some content-based image properties. The conventional feature representations aggregate and store these properties in global feature histograms (e.g.,
MPEG-7 visual descriptors).

Recent feature representations, however, adaptively aggregate local image features in more flexible feature signatures, which can be
compared by adaptive similarity measures. The SIR engine developed at SIRET research group combines traditional MPEG-7 visual descriptors with feature signatures, leading to improved similarity search in image collections.

Currently, the SIR engine operates in a demo mode as a standalone image search engine. In order to manage large image collections in real time, the engine employs original database indexing technology. The SIR engine also includes meta-search functionality that allows to augment/rerank/explore results provided by other image search engines, such as Google Images and others. The actual version of the online re-ranking and exploration tool employes the particle physics model, that both distributes images on the screen and automatically creates visually similar clusters (as a side effect). To refer this tool, you can refer our publications - Image Exploration using Online Feature Extraction and Reranking (ICMR, 2012) and SIR: The Smart Image Retrieval Engine (SISAP, 2012).

Developers: 
jakub.lokoc
tomas.skopal

David Hoksza

Name: 
David
Surname: 
Hoksza
Homepage: 
http://siret.ms.mff.cuni.cz/members/hoksza
Research interests: 
  • bioinformatics
  • structural bioinformatics
  • cheminformatics
  • protein and RNA databases
Type of member: 
Staff
State: 
Active

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