About: On Optimizing the Non-metric Similarity Search in Tandem Mass Spectra by Clustering

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://dx.doi.org/10.1007/978-3-642-30191-9_18
Description	Tandem mass spectrometry is a well-known technique for identification of protein sequences from an %22in vitro%22 sample. To identify the sequences from spectra captured by a spectrometer, the similarity search in a database of hypothetical mass spectra is often used. For this purpose, a database of known protein sequences is utilized to generate the hypothetical spectra. Since the number of sequences in the databases grows rapidly over the time, several approaches have been proposed to index the databases of mass spectra. In this paper, we improve an approach based on the non-metric similarity search where the M-tree and the TriGen algorithm are employed for fast and approximative search. We show that preprocessing of mass spectra by clustering speeds up the identification of sequences more than 100x with respect to the sequential scan of the entire database. Moreover, when the protein candidates are refined by sequential scan in the postprocessing step, the whole approach exhibits precision similar to that of sequential scan over the entire database (over 90%). Tandem mass spectrometry is a well-known technique for identification of protein sequences from an %22in vitro%22 sample. To identify the sequences from spectra captured by a spectrometer, the similarity search in a database of hypothetical mass spectra is often used. For this purpose, a database of known protein sequences is utilized to generate the hypothetical spectra. Since the number of sequences in the databases grows rapidly over the time, several approaches have been proposed to index the databases of mass spectra. In this paper, we improve an approach based on the non-metric similarity search where the M-tree and the TriGen algorithm are employed for fast and approximative search. We show that preprocessing of mass spectra by clustering speeds up the identification of sequences more than 100x with respect to the sequential scan of the entire database. Moreover, when the protein candidates are refined by sequential scan in the postprocessing step, the whole approach exhibits precision similar to that of sequential scan over the entire database (over 90%). (en)
Title	On Optimizing the Non-metric Similarity Search in Tandem Mass Spectra by Clustering On Optimizing the Non-metric Similarity Search in Tandem Mass Spectra by Clustering (en)
skos:prefLabel	On Optimizing the Non-metric Similarity Search in Tandem Mass Spectra by Clustering On Optimizing the Non-metric Similarity Search in Tandem Mass Spectra by Clustering (en)
skos:notation	RIV/00216208:11320/12:10124006!RIV13-GA0-11320___
http://linked.open...avai/riv/aktivita	P S
http://linked.open...avai/riv/aktivity	P(GAP202/11/0968), P(GD201/09/H057), P(GPP202/12/P297), S
http://linked.open...iv/cisloPeriodika	7292
http://linked.open...vai/riv/dodaniDat	2013
http://linked.open...aciTvurceVysledku	Lokoč, Jakub Skopal, Tomáš Hoksza, David Novák, Jiří
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Univerzita Karlova v Praze / Matematicko-fyzikální fakulta
http://linked.open...dnocenehoVysledku	156288
http://linked.open...ai/riv/idVysledku	RIV/00216208:11320/12:10124006
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	spectral clustering; protein sequences identification; non-metric access methods; similarity search; tandem mass spectrometry (en)
http://linked.open.../riv/klicoveSlovo	similarity search tandem mass spectrometry non-metric access methods protein sequences identification spectral clustering
http://linked.open...odStatuVydavatele	DE - Spolková republika Německo
http://linked.open...ontrolniKodProRIV	[883758329391]
http://linked.open...i/riv/nazevZdroje	Lecture Notes in Computer Science
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	4 (xsd:int)
http://linked.open...cetTvurcuVysledku	4 (xsd:int)
http://linked.open...vavai/riv/projekt	Large-scale Nonmetric Similarity Search in Complex Domains Res Informatica Synergické modelování adaptivních podobnostních měr pro potřeby multimediálního vyhledávání
http://linked.open...UplatneniVysledku	2012
http://linked.open...v/svazekPeriodika	2012
http://linked.open...iv/tvurceVysledku	Lokoč, Jakub Novák, Jiří Skopal, Tomáš Hoksza, David
issn	0302-9743
number of pages	12 (xsd:int)
http://bibframe.org/vocab/doi	10.1007/978-3-642-30191-9_18
http://localhost/t...ganizacniJednotka	11320

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