Comparing distance metrics for rotation using the k-nearest neighbors algorithm for entropy estimation

Copyright © 2013 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc.

Bibliographische Detailangaben
Veröffentlicht in:Journal of computational chemistry. - 1984. - 35(2014), 5 vom: 15. Feb., Seite 377-85
1. Verfasser: Huggins, David J (VerfasserIn)
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2014
Zugriff auf das übergeordnete Werk:Journal of computational chemistry
Schlagworte:Comparative Study Journal Article Research Support, Non-U.S. Gov't distance metric entropy k-nearest neighbors molecular dynamics solvation statistical mechanics Water 059QF0KO0R
LEADER 01000caa a22002652 4500
001 NLM23340466X
003 DE-627
005 20240321233200.0
007 cr uuu---uuuuu
008 231224s2014 xx |||||o 00| ||eng c
024 7 |a 10.1002/jcc.23504  |2 doi 
028 5 2 |a pubmed24n1338.xml 
035 |a (DE-627)NLM23340466X 
035 |a (NLM)24311273 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Huggins, David J  |e verfasserin  |4 aut 
245 1 0 |a Comparing distance metrics for rotation using the k-nearest neighbors algorithm for entropy estimation 
264 1 |c 2014 
336 |a Text  |b txt  |2 rdacontent 
337 |a ƒaComputermedien  |b c  |2 rdamedia 
338 |a ƒa Online-Ressource  |b cr  |2 rdacarrier 
500 |a Date Completed 05.09.2014 
500 |a Date Revised 21.03.2024 
500 |a published: Print-Electronic 
500 |a Citation Status MEDLINE 
520 |a Copyright © 2013 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc. 
520 |a Distance metrics facilitate a number of methods for statistical analysis. For statistical mechanical applications, it is useful to be able to compute the distance between two different orientations of a molecule. However, a number of distance metrics for rotation have been employed, and in this study, we consider different distance metrics and their utility in entropy estimation using the k-nearest neighbors (KNN) algorithm. This approach shows a number of advantages over entropy estimation using a histogram method, and the different approaches are assessed using uniform randomly generated data, biased randomly generated data, and data from a molecular dynamics (MD) simulation of bulk water. The results identify quaternion metrics as superior to a metric based on the Euler angles. However, it is demonstrated that samples from MD simulation must be independent for effective use of the KNN algorithm and this finding impacts any application to time series data 
650 4 |a Comparative Study 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
650 4 |a distance metric 
650 4 |a entropy 
650 4 |a k-nearest neighbors 
650 4 |a molecular dynamics 
650 4 |a solvation 
650 4 |a statistical mechanics 
650 7 |a Water  |2 NLM 
650 7 |a 059QF0KO0R  |2 NLM 
773 0 8 |i Enthalten in  |t Journal of computational chemistry  |d 1984  |g 35(2014), 5 vom: 15. Feb., Seite 377-85  |w (DE-627)NLM098138448  |x 1096-987X  |7 nnns 
773 1 8 |g volume:35  |g year:2014  |g number:5  |g day:15  |g month:02  |g pages:377-85 
856 4 0 |u http://dx.doi.org/10.1002/jcc.23504  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 35  |j 2014  |e 5  |b 15  |c 02  |h 377-85