dc.contributor.author
Haack, Fiete
dc.contributor.author
Fackeldey, Konstantin
dc.contributor.author
Röblitz, Susanna
dc.contributor.author
Scharkoi, Olga
dc.contributor.author
Weber, Marcus
dc.contributor.author
Schmidt, Burkhard
dc.date.accessioned
2018-06-08T03:43:36Z
dc.date.available
2015-11-25T09:11:59.761Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/15799
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-19986
dc.description.abstract
A decomposition of a molecular conformational space into sets or functions
(states) allows for a reduced description of the dynamical behavior in terms
of transition probabilities between these states. Spectral clustering of the
corresponding transition probability matrix can then reveal metastabilities.
The more states are used for the decomposition, the smaller the risk to cover
multiple conformations with one state, which would make these conformations
indistinguishable. However, since the computational complexity of the
clustering algorithm increases quadratically with the number of states, it is
desirable to have as few states as possible. To balance these two
contradictory goals, we present an algorithm for an adaptive decomposition of
the position space starting from a very coarse decomposition. The algorithm is
applied to small data classification problems where it was shown to be
superior to commonly used algorithms, e.g., k-means. We also applied this
algorithm to the conformation analysis of a tripeptide molecule where six-
dimensional time series are successfully analyzed.
en
dc.rights.uri
http://publishing.aip.org/authors/web-posting-guidelines
dc.subject.ddc
500 Naturwissenschaften und Mathematik::540 Chemie
dc.title
Adaptive spectral clustering with application to tripeptide conformation
analysis
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation
Journal of Chemical Physics. - 139 (2013), 19, Artikel Nr. 194110
dcterms.bibliographicCitation.doi
10.1063/1.4830409
dcterms.bibliographicCitation.url
http://dx.doi.org/10.1063/1.4830409
refubium.affiliation
Mathematik und Informatik
de
refubium.funding
OpenAccess Publikation in Allianzlizenz
refubium.mycore.fudocsId
FUDOCS_document_000000023523
refubium.resourceType.isindependentpub
no
refubium.mycore.derivateId
FUDOCS_derivate_000000005708
dcterms.accessRights.openaire
open access