DocumentCode
1645006
Title
A Kohonen self-organizing map for the functional classification of proteins based on one-dimensional sequence information
Author
Pollock, Robert ; Lane, Toby ; Watts, Michael
Author_Institution
Dept. of Biochem., Otago Univ., Dunedin, New Zealand
Volume
1
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
189
Lastpage
192
Abstract
There are many examples where neural networks have been effectively used to predict protein secondary and tertiary structure from the primary sequence data. We describe the use of a Kohonen self-organizing map (SOM) to categorise proteins based on secondary structure, and attempt to relate this information to functional data
Keywords
biology computing; learning (artificial intelligence); molecular biophysics; proteins; self-organising feature maps; sequences; Kohonen self-organizing map; functional classification; functional data; one-dimensional sequence information; primary sequence data; protein secondary structure; protein tertiary structure; proteins; Amino acids; Biochemistry; Information science; Knowledge engineering; Laboratories; Libraries; Neural networks; Organisms; Protein engineering; Sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location
Honolulu, HI
ISSN
1098-7576
Print_ISBN
0-7803-7278-6
Type
conf
DOI
10.1109/IJCNN.2002.1005467
Filename
1005467
Link To Document