RUDOLFOVÁ, Ivana, Jaroslav ZENDULKA and Matej LEXA. Clustering of Protein Substructures for Discovery of a Novel Class of Sequence-Structure Fragments. In ITBAM 2010 (Information Technology in Bio- and Medical Informatics), LNCS 6266. Heidelberg, DE: Springer Verlag, 2010. p. 94-101, 8 pp. ISBN 978-3-642-15019-7. doi:10.1007/978-3-642-15020-3_9.
Other formats:   BibTeX LaTeX RIS
Basic information
Original name Clustering of Protein Substructures for Discovery of a Novel Class of Sequence-Structure Fragments
Name in Czech Shlukování proteinových substruktur pro nalezení nových sekvenčně-strukturních fragmentů
Authors RUDOLFOVÁ, Ivana (203 Czechia, guarantor), Jaroslav ZENDULKA (203 Czechia) and Matej LEXA (703 Slovakia, belonging to the institution).
Edition Heidelberg, DE, ITBAM 2010 (Information Technology in Bio- and Medical Informatics), LNCS 6266, p. 94-101, 8 pp. 2010.
Publisher Springer Verlag
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Germany
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
Impact factor Impact factor: 0.402 in 2005
RIV identification code RIV/00216224:14330/10:00067213
Organization unit Faculty of Informatics
ISBN 978-3-642-15019-7
ISSN 0302-9743
Doi http://dx.doi.org/10.1007/978-3-642-15020-3_9
UT WoS 000286166000009
Keywords in English Clustering; density-based clustering; clustering of protein substructures; sequence-structure relationships in proteins
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 30/4/2014 04:25.
Abstract
In this paper, we propose a novel method for clustering of protein substructures that we developed to study the relationships between protein sequences and their corresponding structures. We show the basic properties of the new method and the results of the comparison to other commonly used methods for clustering of protein structures. The main advantage of our method is its high efficiency and scalability, which are key factors for analyzing large data sets. Finally, we outline a procedure for finding sequence profiles that tend to occur in more than one structural conformation but the number of their structural conformations is limited. This procedure is based on our method for protein substructure clustering.
Links
MSM0021622419, plan (intention)Name: Vysoce paralelní a distribuované výpočetní systémy
Investor: Ministry of Education, Youth and Sports of the CR, Research Intents
PrintDisplayed: 15/8/2020 13:58