Sammanfattning
This paper evaluates whether shape features can be used for clustering objects in Sidec (tm), Electron Tomography (SET) reconstructions. SET reconstructions contain a large number of objects, and only a few of them are of interest. It is desired to limit the analysis to contain as few uninteresting objects as possible. Unsupervised hierarchical clustering is used to group objects into classes. Experiments are done on one synthetic data set and two data sets from a SET reconstruction of a human growth hormone (1hwg) in solution. The experiments indicate that clustering of objects in SET reconstructions based on shape features is useful for finding structural classes
Nyckelord
clustering; shape; electron tomography; protein
Publicerad i
Lecture Notes in Computer Science
2005, volym: 3687, sidor: 377-380
Konferens
Third International Conference on Advances in Pattern Recognition, ICAPR 2005
UKÄ forskningsämne
Datorgrafik och datorseende
Publikationens identifierare
- ISBN: 3-540-28833-3
Permanent länk till denna sida (URI)
https://res.slu.se/id/publ/8353