Proteins networks

JM Chandoma, M Karplus. The importance of larger data sets for protein secondary structure prediction with neural networks. Protein Sci 5 768-774, 1996. 

McGregor, M.J., Flores, T.P. and Sternberg, M.J.E. (1989) Prediction of -tums in proteins using a neural network. Protein Engineering, 2, 521-526. 

Figure 3.2 The molecular arrangement of the cell membrane (A) integral proteins (B) glycoprotein (C) pore formed from integral protein (D) various phospholipids with saturated fatty acid chains (E) phospholipids with unsaturated fatty acid chains (F) network proteins (G) cholesterol (H) glycolipid (I) peripheral protein. There are four different phospholipids phosphatidyl serine phosphatidyl choline phosphatidyl ethanolamine and sphingomyelin represented as , o. The stippled area of the protein represents the hydrophobic portion. Source From Ref. 1.

Figure 12.6. Secondary structure prediction of duck lysozyme at NPS . The predicted secondary structures of duck lysozyme at Network Protein Sequence Analysis (NPS ) with GOR IV method are depicted in different representations.

Figure 12,7. Secondary structure consensus prediction at NPS . Network Protein Sequence Analysis (NPS ) offers numerous methods for secondary structure prediction of proteins. The secondary structure consensus prediction (Sec.Cons.) of duck lysozyme is derived from simultaneous execution of predictions with more than one methods.

Saha S, Raghava G (2006) Prediction of continuous B-cell epitopes in an antigen using recurrent neural network. Proteins 65 40-48... 

V. Detours, and S. Brunak. Prediction of proteasome cleavage motifs by neural networks. Protein Engineering, 15 287-296, 2002. 

Part II of this book represents the bulk of the material on the analysis and modeling of biochemical systems. Concepts covered include biochemical reaction kinetics and kinetics of enzyme-mediated reactions simulation and analysis of biochemical systems including non-equilibrium open systems, metabolic networks, and phosphorylation cascades transport processes including membrane transport and electrophysiological systems. Part III covers the specialized topics of spatially distributed transport modeling and blood-tissue solute exchange, constraint-based analysis of large-scale biochemical networks, protein-protein interactions, and stochastic systems. 

Special topics - explores spatially distributed systems, constraint-based analysis for large-scale networks, protein-protein interaction, and stochastic phenomena in biochemical... 

Schuchhardt, J., Schneider, G., Reichelt, J., Schomberg, D. Wrede, P. (1996). Local structural motifs of protein backbones are classified by self-organizing neural networks. Protein Eng 9, 833-42. 

Blom, N Hansen, J., Blaas, D. Brunak, S. (1996). Cleavage site analysis in picomaviral polyproteins discovering cellular targets by neural networks. Protein Sci 5,2203-16. 

Pereira-Leal, J.B., Enright, A.J. and Ouzounis, C.A. (2004) Detection of functional modules from protein interaction networks. Proteins 54, 49-57. 

Hazburn, T.R. and Fields, S. 2001. Networking proteins in yeast. Proc. Natl. Acad. Sci. USA 98, 4277-4278. 

A. J. Shepherd, D. Gorse, J. M. Thornton. Prediction of the location and type of beta-turns in proteins using neural networks. Protein Sci. 1999, 8, 1045-1055. 

Stahl, M., Taroni, C. Schneider, G. (2000). Mapping of protein surface cavities and prediction of enzyme class by a self-organizing neural network. Protein Eng 13(2), 83-8. 

Ehrlich, L., Reczko, M., Bohr, H., and Wade, R.C. (1998) Prediction of protein hydration sites from sequence by modular neural networks. Protein Engineering, 11, 11-19. 

The statistical methods for predicting secondary structures of proteins from amino acid sequences are widely practiced among investigators in biochemistry and can be accessed at Network Protein Sequence Analysis (NPS ) via http //npsa-pbil.ibcp.fr... 

Andrade, M.A., Chacon, P., Merelo, J.J., Moran, F. Evaluation of secondary structure of proteins from UV circular dichroism spectra using an unsupervised learning neural network Protein Eng. 6, 383-390 (1993)... 

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