DocumentCode :
1915514
Title :
A clustering method of chromosome fluorescence profiles by modified self organizing map
Author :
Douzono, Hiroshi ; Hara, Shigeomi ; Eishima, Sumiko ; Noguchi, Yoshio
Author_Institution :
Dept. of Sci. & Eng., Saga Univ., Japan
Volume :
5
fYear :
1999
fDate :
1999
Firstpage :
3614
Abstract :
The clustering by the self-organizing map algorithm of chromosome profiles measured by slit-scan flowcytometer is proposed. Moreover, the physical models of chromosomes have been introduced in order to take into account the rotation of chromosomes in the flowcytometer. The self-organizing map algorithm has been improved so that it can modify the characteristic parameters of chromosome physical models. By this modification, the lengths of chromosomes and the intensity distribution of chromosome fluorescence can be estimated from chromosome profile data measured by the flowcytometer. The estimated lengths of chromosomes are almost equal to known values of the lengths of chromosomes. The clustering results by the above method are compared with the clustering results of the same data by the K-mean method and agglomerative hierarchical clustering
Keywords :
DNA; biology computing; cellular biophysics; learning (artificial intelligence); pattern classification; self-organising feature maps; DNA; chromosome fluorescence; clustering; learning; self organizing map; slit-scan flowcytometer; Bioinformatics; Biological cells; Clustering algorithms; Clustering methods; Fluorescence; Genomics; Length measurement; Organizing; Sampling methods; Sorting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
ISSN :
1098-7576
Print_ISBN :
0-7803-5529-6
Type :
conf
DOI :
10.1109/IJCNN.1999.836254
Filename :
836254
Link To Document :
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