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Statements

Subject Item
n2:RIV%2F61989100%3A27240%2F10%3A86075394%21RIV11-MSM-27240___
rdf:type
skos:Concept n17:Vysledek
dcterms:description
In this paper, we present a novel algorithm for measuring protein similarity based on their 3-D structure (protein tertiary structure). The algorithm used a suffix tree for discovering common parts of main chains of all proteins appearing in the current research collaboratory for structural bioinformatics protein data bank (PDB). By identifying these common parts, we build a vector model and use some classical information retrieval (IR) algorithms based on the vector model to measure the similarity between proteins-all to all protein similarity. For the calculation of protein similarity, we use term frequency x inverse document frequency (tf x idf) term weighing schema and cosine similarity measure. The goal of this paper is to introduce new protein similarity metric based on suffix trees and IR methods. Whole current PDB database was used to demonstrate very good time complexity of the algorithm as well as high precision. In this paper, we present a novel algorithm for measuring protein similarity based on their 3-D structure (protein tertiary structure). The algorithm used a suffix tree for discovering common parts of main chains of all proteins appearing in the current research collaboratory for structural bioinformatics protein data bank (PDB). By identifying these common parts, we build a vector model and use some classical information retrieval (IR) algorithms based on the vector model to measure the similarity between proteins-all to all protein similarity. For the calculation of protein similarity, we use term frequency x inverse document frequency (tf x idf) term weighing schema and cosine similarity measure. The goal of this paper is to introduce new protein similarity metric based on suffix trees and IR methods. Whole current PDB database was used to demonstrate very good time complexity of the algorithm as well as high precision.
dcterms:title
Searching Protein 3-D Structures for Optimal Structure Alignment Using Intelligent Algorithms and Data Structures Searching Protein 3-D Structures for Optimal Structure Alignment Using Intelligent Algorithms and Data Structures
skos:prefLabel
Searching Protein 3-D Structures for Optimal Structure Alignment Using Intelligent Algorithms and Data Structures Searching Protein 3-D Structures for Optimal Structure Alignment Using Intelligent Algorithms and Data Structures
skos:notation
RIV/61989100:27240/10:86075394!RIV11-MSM-27240___
n3:aktivita
n13:S
n3:aktivity
S
n3:cisloPeriodika
6
n3:dodaniDat
n6:2011
n3:domaciTvurceVysledku
Abraham Padath, Ajith n15:4347269
n3:druhVysledku
n12:J
n3:duvernostUdaju
n16:S
n3:entitaPredkladatele
n10:predkladatel
n3:idSjednocenehoVysledku
286577
n3:idVysledku
RIV/61989100:27240/10:86075394
n3:jazykVysledku
n11:eng
n3:klicovaSlova
Structures; Data; and; Algorithms; Intelligent; Using; Alignment; Structure; Optimal; for; Structures; 3-D; Protein; Searching
n3:klicoveSlovo
n4:3-D n4:Using n4:Structure n4:Structures n4:Searching n4:Data n4:Intelligent n4:Optimal n4:for n4:Alignment n4:and n4:Protein n4:Algorithms
n3:kodStatuVydavatele
US - Spojené státy americké
n3:kontrolniKodProRIV
[385B2A8E12E7]
n3:nazevZdroje
IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE
n3:obor
n7:IN
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
4
n3:rokUplatneniVysledku
n6:2010
n3:svazekPeriodika
14
n3:tvurceVysledku
Yang, Jack Y. Abraham Padath, Ajith Novosád, Tomáš Snášel, Václav
n3:wos
000283982200008
s:issn
1089-7771
s:numberOfPages
9
n5:organizacniJednotka
27240