Efficient computation of root mean square deviations under rigid transformations
- Publikationstyp:
- Zeitschriftenaufsatz
- Metadaten:
-
- Autoren
- Anna Katharina Hildebrandt
- Matthias Dietzen
- Thomas Lengauer
- Hans-Peter Lenhof
- Ernst Althaus
- Andreas Hildebrandt
- Sammlungen
- metadata
- ISSN
- 0192-8651
- Ausgabe der Veröffentlichung
- 10
- Zeitschrift
- Journal of computational chemistry
- Schlüsselwörter
- 004 Informatik
- 004 Data processing
- Sprache
- eng
- Paginierung
- Seiten: 765 - 771
- Datum der Veröffentlichung
- 2014
- Herausgeber
- Wiley
- Herausgeber URL
- http://dx.doi.org/10.1002/jcc.23513
- Datum der Datenerfassung
- 2020
- Datum, an dem der Datensatz öffentlich gemacht wurde
- 2020
- Zugang
- Public
- Titel
- Efficient computation of root mean square deviations under rigid transformations
- Ausgabe der Zeitschrift
- 35
Datenquelle: METADATA.UB
- Andere Metadatenquellen:
-
- Autoren
- Anna K Hildebrandt
- Matthias Dietzen
- Thomas Lengauer
- Hans-Peter Lenhof
- Ernst Althaus
- Andreas Hildebrandt
- Autoren-URL
- https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000332446300001&DestLinkType=FullRecord&DestApp=WOS_CPL
- DOI
- 10.1002/jcc.23513
- eISSN
- 1096-987X
- Externe Identifier
- Clarivate Analytics Document Solution ID: AC3UI
- PubMed Identifier: 24356990
- ISSN
- 0192-8651
- Ausgabe der Veröffentlichung
- 10
- Zeitschrift
- JOURNAL OF COMPUTATIONAL CHEMISTRY
- Schlüsselwörter
- protein docking
- root mean square deviation computation
- molecular modeling
- Paginierung
- 765 - 771
- Datum der Veröffentlichung
- 2014
- Status
- Published
- Titel
- Efficient Computation of Root Mean Square Deviations Under Rigid Transformations
- Sub types
- Article
- Ausgabe der Zeitschrift
- 35
Datenquelle: Web of Science (Lite)
- Abstract
- <jats:p>The computation of root mean square deviations (RMSD) is an important step in many bioinformatics applications. If approached naively, each RMSD computation takes time linear in the number of atoms. In addition, a careful implementation is required to achieve numerical stability, which further increases runtimes. In practice, the structural variations under consideration are often induced by rigid transformations of the protein, or are at least dominated by a rigid component. In this work, we show how RMSD values resulting from rigid transformations can be computed in constant time from the protein's covariance matrix, which can be precomputed in linear time. As a typical application scenario is protein clustering, we will also show how the Ward‐distance which is popular in this field can be reduced to RMSD evaluations, yielding a constant time approach for their computation. © 2014 Wiley Periodicals, Inc.</jats:p>
- Autoren
- Anna K Hildebrandt
- Matthias Dietzen
- Thomas Lengauer
- Hans‐Peter Lenhof
- Ernst Althaus
- Andreas Hildebrandt
- DOI
- 10.1002/jcc.23513
- eISSN
- 1096-987X
- ISSN
- 0192-8651
- Ausgabe der Veröffentlichung
- 10
- Zeitschrift
- Journal of Computational Chemistry
- Sprache
- en
- Online publication date
- 2013
- Paginierung
- 765 - 771
- Datum der Veröffentlichung
- 2014
- Status
- Published
- Herausgeber
- Wiley
- Herausgeber URL
- http://dx.doi.org/10.1002/jcc.23513
- Datum der Datenerfassung
- 2023
- Titel
- Efficient computation of root mean square deviations under rigid transformations
- Ausgabe der Zeitschrift
- 35
Datenquelle: Crossref
- Abstract
- The computation of root mean square deviations (RMSD) is an important step in many bioinformatics applications. If approached naively, each RMSD computation takes time linear in the number of atoms. In addition, a careful implementation is required to achieve numerical stability, which further increases runtimes. In practice, the structural variations under consideration are often induced by rigid transformations of the protein, or are at least dominated by a rigid component. In this work, we show how RMSD values resulting from rigid transformations can be computed in constant time from the protein's covariance matrix, which can be precomputed in linear time. As a typical application scenario is protein clustering, we will also show how the Ward-distance which is popular in this field can be reduced to RMSD evaluations, yielding a constant time approach for their computation.
- Addresses
- Center for Bioinformatics, Saarland University, Saarbrücken, 66041, Germany.
- Autoren
- Anna K Hildebrandt
- Matthias Dietzen
- Thomas Lengauer
- Hans-Peter Lenhof
- Ernst Althaus
- Andreas Hildebrandt
- DOI
- 10.1002/jcc.23513
- eISSN
- 1096-987X
- Externe Identifier
- PubMed Identifier: 24356990
- Open access
- false
- ISSN
- 0192-8651
- Ausgabe der Veröffentlichung
- 10
- Zeitschrift
- Journal of computational chemistry
- Schlüsselwörter
- Proteins
- Computational Biology
- Protein Conformation
- Computer Simulation
- Sprache
- eng
- Medium
- Print-Electronic
- Online publication date
- 2013
- Paginierung
- 765 - 771
- Datum der Veröffentlichung
- 2014
- Status
- Published
- Datum der Datenerfassung
- 2013
- Titel
- Efficient computation of root mean square deviations under rigid transformations.
- Sub types
- Research Support, Non-U.S. Gov't
- Journal Article
- Ausgabe der Zeitschrift
- 35
Datenquelle: Europe PubMed Central
- Abstract
- The computation of root mean square deviations (RMSD) is an important step in many bioinformatics applications. If approached naively, each RMSD computation takes time linear in the number of atoms. In addition, a careful implementation is required to achieve numerical stability, which further increases runtimes. In practice, the structural variations under consideration are often induced by rigid transformations of the protein, or are at least dominated by a rigid component. In this work, we show how RMSD values resulting from rigid transformations can be computed in constant time from the protein's covariance matrix, which can be precomputed in linear time. As a typical application scenario is protein clustering, we will also show how the Ward-distance which is popular in this field can be reduced to RMSD evaluations, yielding a constant time approach for their computation.
- Date of acceptance
- 2013
- Autoren
- Anna K Hildebrandt
- Matthias Dietzen
- Thomas Lengauer
- Hans-Peter Lenhof
- Ernst Althaus
- Andreas Hildebrandt
- Autoren-URL
- https://www.ncbi.nlm.nih.gov/pubmed/24356990
- DOI
- 10.1002/jcc.23513
- eISSN
- 1096-987X
- Ausgabe der Veröffentlichung
- 10
- Zeitschrift
- J Comput Chem
- Schlüsselwörter
- molecular modeling
- protein docking
- root mean square deviation computation
- Computational Biology
- Computer Simulation
- Protein Conformation
- Proteins
- Sprache
- eng
- Country
- United States
- Paginierung
- 765 - 771
- Datum der Veröffentlichung
- 2014
- Status
- Published
- Datum, an dem der Datensatz öffentlich gemacht wurde
- 2016
- Titel
- Efficient computation of root mean square deviations under rigid transformations.
- Sub types
- Journal Article
- Research Support, Non-U.S. Gov't
- Ausgabe der Zeitschrift
- 35
Datenquelle: PubMed
- Autoren
- Anna Katharina Hildebrandt
- Matthias Dietzen
- Thomas Lengauer
- Hans-Peter Lenhof
- Ernst Althaus
- Andreas Hildebrandt
- DOI
- 10.1002/jcc.23513
- Zeitschrift
- J. Comput. Chem.
- Artikelnummer
- 10
- Paginierung
- 765 - 771
- Datum der Veröffentlichung
- 2014
- Titel
- Efficient computation of root mean square deviations under rigid transformations.
- Ausgabe der Zeitschrift
- 35
Datenquelle: DBLP
- Autoren
- Anna K Hildebrandt
- Matthias Dietzen
- Thomas Lengauer
- Hans-Peter Lenhof
- Ernst Althaus
- Andreas Hildebrandt
- Zeitschrift
- Journal of computational chemistry
- Artikelnummer
- 10
- Paginierung
- 765 - 771
- Datum der Veröffentlichung
- 2014
- Datum der Datenerfassung
- 2020
- Titel
- Efficient computation of root mean square deviations under rigid transformations
- Sub types
- article
- Ausgabe der Zeitschrift
- 35
Datenquelle: Manual
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