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SIGMOD

Research area: 
Databases
Publisher: 
ACM

Jiří Novák

Name: 
Jiří
Surname: 
Novák
Homepage: 
http://siret.ms.mff.cuni.cz/novak/
Research interests: 
  • mass spectrometry
  • similarity search and metric access methods
Type of member: 
External
State: 
Active

Juraj Moško

Name: 
Juraj
Surname: 
Moško
Homepage: 
http://siret.ms.mff.cuni.cz/mosko/
Research interests: 
  • similarity search
  • metric and nonmetric indexing
  • real time queries in multimedia databases
Type of member: 
Student
State: 
Former

Martin Kruliš

Name: 
Martin
Surname: 
Kruliš
Homepage: 
http://www.ksi.mff.cuni.cz/%7Ekrulis/
Research interests: 
  • parallelism and parallel architectures
  • general purpose GPU computing
  • databases, representation and processing of semi-structured and structured data
Type of member: 
Staff
State: 
Active

Tomáš Grošup

Name: 
Tomáš
Surname: 
Grošup
Homepage: 
http://siret.ms.mff.cuni.cz/grosup/
Research interests: 
  • similarity search in metric and nonmetric spaces
  • multimedia databases
Type of member: 
Student
State: 
Active

Jakub Galgonek

Name: 
Jakub
Surname: 
Galgonek
Homepage: 
http://siret.ms.mff.cuni.cz/members/galgonek/
Research interests: 
  • structural bioinformatics
  • searching in protein structure databases
  • protein structure classification and prediction
Type of member: 
External
State: 
Active

Tomáš Bartoš

Name: 
Tomáš
Surname: 
Bartoš
Homepage: 
http://siret.ms.mff.cuni.cz/bartos/
Research interests: 
  • similarity searching in (non)metric spaces
  • multimedia databases
  • information retrieval
  • XML
Type of member: 
Student
State: 
Former

Jakub Lokoč

Name: 
Jakub
Surname: 
Lokoč
Homepage: 
http://siret.ms.mff.cuni.cz/lokoc/
Research interests: 
  • similarity search in unstructured data
  • metric and nonmetric indexing
  • content based retrieval
  • multimedia databases
Type of member: 
Staff
State: 
Active

Alan Eckhardt

Name: 
Alan
Surname: 
Eckhardt
Homepage: 
http://www.ksi.mff.cuni.cz/%7Eeckhardt/
Research interests: 
  • machine learning
  • user preferences
  • data mining
Type of member: 
Staff
State: 
Former

Simtandem

Type: 
Bioinformatics & Cheminformatics
One line description: 
Protein sequence identification
Annotation: 

SimTandem is a tool for protein or peptide sequences identification from tandem mass spectra. The identification is based on the similarity search in databases of already known or predicted protein sequences. Since the size of sequence databases grows rapidly, metric access methods are employed for database indexes. SimTandem implements a previously proposed method, where the M-tree and the TriGen algorithm were used for fast and approximative (i.e., non-metric) search. The recently introduced parameterized Hausdorff distance, which is suitable as a coarse filter for metric indexes, is utilized. SimTandem supports the search of mass spectra with posttranslational modifications, which are quite common problem when mass spectra are interpreted. SimTandem has been implemented as both the on-line web tool and the stand-alone application. SimTandem is freely available at http://www.simtandem.org or http://www.siret.cz/simtandem.

Developers: 
jiri.novak
tomas.skopal
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