Title :
Application of Stochastic Proximity Embedding to Distance Geometry Problems
Author :
Kashima, Hiroyuki ; DOI, Shinji ; Kumagai, Sadatoshi
Author_Institution :
Graduate Sch. of Eng., Osaka Univ.
Abstract :
We extend the stochastic proximity embedding (SPE) method which was proposed as a method of data-mining, and apply it to distance geometry problems. Distance geometry problems are the problem that we calculate the coordinates of atoms from the distance data between atoms. We also propose an improvement of SPE and demonstrate its effectiveness in determining protein structures
Keywords :
biology computing; data mining; data visualisation; geometry; molecular biophysics; molecular configurations; proteins; data visualization; data-mining; distance geometry problems; protein structures; stochastic proximity embedding; Data engineering; Euclidean distance; Geometry; Machine learning; Magnetic analysis; Nuclear magnetic resonance; Optimization methods; Proteins; Statistics; Stochastic processes; data-mining; nuclear magnetic resonance analysis; optimization method; protein-structure determination;
Conference_Titel :
SICE-ICASE, 2006. International Joint Conference
Conference_Location :
Busan
Print_ISBN :
89-950038-4-7
Electronic_ISBN :
89-950038-5-5
DOI :
10.1109/SICE.2006.314780
