On postprocessing of neural network prediction of polyproline type II secondary structures: Network spectrum, response analysis, and scattering

Neural Computing and Applications

Volumn 11, Issue 3-4, 2003, Pages 238-243

  Siermala, M ^a   Vihinen, M ^b,c   Juhola, M ^a  

^a TAMPERE UNIVERSITY OF TECHNOLOGY   (Finland)

^b UNIVERSITY OF TAMPERE   (Finland)

^c TAMPERE UNIVERSITY HOSPITAL   (Finland)

Author keywords

Analysis of prediction results; Neural networks; Polyproline type II; Postprocessing of neural network results; Protein secondary structures

Indexed keywords

BACKPROPAGATION; DECISION MAKING; LEARNING ALGORITHMS; LEARNING SYSTEMS; SPECTRUM ANALYSIS;

HAMMING DISTANCES; NETWORK SPECTRUM; PROTEIN SECONDARY STRUCTURES; RESPONSE ANALYSIS;

NEURAL NETWORKS;

EID: 0038792228     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-003-0360-5     Document Type: Article

References (12)

1. Siermala M, Juhola M, Vihinen M. Neural network prediction of polyproline type II secondary structures. In: Hasman A, Blobel B, Dudeck J, Engelbrecht R, Gell G, Prokosch H-U (eds), Medical Infobahn for Europe, Proc MIE2000 and GMDS2000, Studies in Health Technology and Informatics, vol 77, IOS Press, Amsterdam, 2000; 475-479
2. PDB http://www.rcsb.og/pdb/
3. Berman H, Westbrook J. Feng Z, Gilliland G, Bhat T, Wessig H, Shindyalov I, Bourne P. The Protein Data Bank, Nucleic Acids Res 2000; 28: 235-242
4. Bishop CM, Neural Networks for Pattern Recognition. Oxford University Press, UK, 1997
5. Swingler, K. Applying Neural Networks. Academic Press, London, 1996
6. Niederberger C, Pursell SE, Golden RM, A neural network to predict lifespan and new metastases in patients with renal cell cancer. In: Fiesler E, Beale R (eds) Handbook of Neural Computation, Institute of Physics Publishing, Bristol, 1997; G5.4: 1-6
7. Needleman SB, Wunsch CD. A general method applicable to search for similarities in amino-acid sequence of two proteins. J Mol Biol 1970; 48: 443-453
8. Adzhubei A Sternberg M. 1993. Left-handed polyproline II helices commonly occur in globular proteins. J Mol Biol 1993; 229: 472-493
9. Ruggiero C, Sacile R, Rauch G. Peptides secondary structure prediction with neural networks: a criterion for building appropriate learning sets. IEEE Trans Biomed Eng 1993; 40: 1114-1121
10. Rost B. A neural network for prediction of protein secondary structure, In: Fiesler E, Beale R (Eds). Handbook of Neural Computation, Institute of Physics Publishing, Bristol, 1997, pp. G4.1: 1-9.
11. Schalkoff R. Pattern Recognition, John Wiley & Sons, New York, 1992
12. Clote P, Backofen R. Computational Molecular Biology, John Wiley & Sons, New York, 2000