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
fDate :
6/24/1905 12:00:00 AM
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;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1005467
