SProt: sphere-based protein structure similarity algorithm

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F11%3A10099650" target="_blank" >RIV/00216208:11320/11:10099650 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.proteomesci.com/content/9/S1/S20" target="_blank" >http://www.proteomesci.com/content/9/S1/S20</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1186/1477-5956-9-S1-S20" target="_blank" >10.1186/1477-5956-9-S1-S20</a>

Jazyk výsledku

angličtina

Název v původním jazyce

SProt: sphere-based protein structure similarity algorithm

Popis výsledku v původním jazyce

In this paper, we proposed SProt - a novel algorithm for measuring protein structure similarity that puts emphasis on high-quality modeling of local similarities of the amino acids. This is achieved by representing each amino acid by its spatial neighborhood containing close amino acids. The approach leads to good realworld results, especially for superfamily/fold classification accuracy and for precision at high recall levels where we outperform all the compared solutions. The focus on the quality of the modeling results in high computational demands of the method. We resolve this handicap be introduction of SProt access method - a modification of LAESA metric access method - that highly decreases the runtime needed for scanning large datasets of protein structures. The speedup makes SProt competitive with the best contemporary solutions not only concerning the effectiveness but also the efficiency.

Název v anglickém jazyce

SProt: sphere-based protein structure similarity algorithm

Popis výsledku anglicky

In this paper, we proposed SProt - a novel algorithm for measuring protein structure similarity that puts emphasis on high-quality modeling of local similarities of the amino acids. This is achieved by representing each amino acid by its spatial neighborhood containing close amino acids. The approach leads to good realworld results, especially for superfamily/fold classification accuracy and for precision at high recall levels where we outperform all the compared solutions. The focus on the quality of the modeling results in high computational demands of the method. We resolve this handicap be introduction of SProt access method - a modification of LAESA metric access method - that highly decreases the runtime needed for scanning large datasets of protein structures. The speedup makes SProt competitive with the best contemporary solutions not only concerning the effectiveness but also the efficiency.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Proteome Science

ISSN

1477-5956

e-ISSN

—

Svazek periodika

9

Číslo periodika v rámci svazku

—

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

12

Strana od-do

"S20", 1-12

Kód UT WoS článku

000299782200020

EID výsledku v databázi Scopus

—