β Edge strands in protein structure prediction and aggregation
暂无分享,去创建一个
[1] W. Wooster,et al. Crystal structure of , 2005 .
[2] B. Matthews. Comparison of the predicted and observed secondary structure of T4 phage lysozyme. , 1975, Biochimica et biophysica acta.
[3] M J Sternberg,et al. On the conformation of proteins: hydrophobic ordering of strands in beta-pleated sheets. , 1977, Journal of molecular biology.
[4] W. Kabsch,et al. Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features , 1983, Biopolymers.
[5] D. Eisenberg,et al. The hydrophobic moment detects periodicity in protein hydrophobicity. , 1984, Proceedings of the National Academy of Sciences of the United States of America.
[6] M. Sternberg,et al. Prediction of protein secondary structure and active sites using the alignment of homologous sequences. , 1987, Journal of molecular biology.
[7] C. Sander,et al. Database of homology‐derived protein structures and the structural meaning of sequence alignment , 1991, Proteins.
[8] D. Eisenberg,et al. Crystal structure of defensin HNP-3, an amphiphilic dimer: mechanisms of membrane permeabilization. , 1991, Science.
[9] J. Ross Quinlan,et al. C4.5: Programs for Machine Learning , 1992 .
[10] J. Thornton,et al. Identification, classification, and analysis of beta‐bulges in proteins , 1993, Protein science : a publication of the Protein Society.
[11] B. Rost,et al. Prediction of protein secondary structure at better than 70% accuracy. , 1993, Journal of molecular biology.
[12] P. S. Kim,et al. Context is a major determinant of β-sheet propensity , 1994, Nature.
[13] R. King,et al. On the use of machine learning to identify topological rules in the packing of β-strands , 1994 .
[14] R A Sayle,et al. RASMOL: biomolecular graphics for all. , 1995, Trends in biochemical sciences.
[15] J. Kelly,et al. Progress towards understanding β-sheet structure , 1996 .
[16] L. Serpell,et al. The "edge strand" hypothesis: Prediction and test of a mutational "hot-spot" on the transthyretin molecule associated with FAP amyloidogenesis , 1996 .
[17] Tim J. P. Hubbard,et al. SCOP: a structural classification of proteins database , 1998, Nucleic Acids Res..
[18] C Kooperberg,et al. Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions. , 1997, Journal of molecular biology.
[19] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[20] D. Baker,et al. Prediction of local structure in proteins using a library of sequence-structure motifs. , 1998, Journal of molecular biology.
[21] J. Thornton,et al. Determinants of strand register in antiparallel β‐sheets of proteins , 1998, Protein science : a publication of the Protein Society.
[22] J. Thornton,et al. PQS: a protein quaternary structure file server. , 1998, Trends in biochemical sciences.
[23] D Gorse,et al. Prediction of the location and type of β‐turns in proteins using neural networks , 1999, Protein science : a publication of the Protein Society.
[24] L. Gregoret,et al. Context-dependence of Amino Acid Residue Pairing in Antiparallel β-She?ets , 1999 .
[25] D T Jones,et al. Protein secondary structure prediction based on position-specific scoring matrices. , 1999, Journal of molecular biology.
[26] T. N. Bhat,et al. The Protein Data Bank , 2000, Nucleic Acids Res..
[27] Nello Cristianini,et al. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .
[28] D. Haussler,et al. Knowledge-based analysis of microarray gene expression , 2000 .
[29] D Haussler,et al. Knowledge-based analysis of microarray gene expression data by using support vector machines. , 2000, Proceedings of the National Academy of Sciences of the United States of America.
[30] Patrice Koehl,et al. The ASTRAL compendium for protein structure and sequence analysis , 2000, Nucleic Acids Res..
[31] M. Sternberg,et al. Enhanced genome annotation using structural profiles in the program 3D-PSSM. , 2000, Journal of molecular biology.
[32] Chris H. Q. Ding,et al. Multi-class protein fold recognition using support vector machines and neural networks , 2001, Bioinform..
[33] Samy Bengio,et al. SVMTorch: Support Vector Machines for Large-Scale Regression Problems , 2001, J. Mach. Learn. Res..
[34] T. Yeates,et al. Identification of a subunit interface in transthyretin amyloid fibrils: evidence for self-assembly from oligomeric building blocks. , 2001, Biochemistry.
[35] S. Hua,et al. A novel method of protein secondary structure prediction with high segment overlap measure: support vector machine approach. , 2001, Journal of molecular biology.
[36] J. Thornton,et al. Prediction of strand pairing in antiparallel and parallel β‐sheets using information theory , 2002, Proteins.
[37] Kevin Burrage,et al. Prediction of protein solvent accessibility using support vector machines , 2002, Proteins.
[38] T. Yeates,et al. Arrangement of subunits and ordering of β-strands in an amyloid sheet , 2002, Nature Structural Biology.
[39] M. Monti,et al. Topological investigation of amyloid fibrils obtained from β2‐microglobulin , 2002, Protein science : a publication of the Protein Society.
[40] Pierre Baldi,et al. Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles , 2002, Proteins.
[41] M. Hoshino,et al. Mapping the core of the β2-microglobulin amyloid fibril by H/D exchange , 2002, Nature Structural Biology.
[42] Andreas Hoenger,et al. De novo designed peptide-based amyloid fibrils , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[43] B. Rost,et al. Alignments grow, secondary structure prediction improves , 2002, Proteins.
[44] Jaques Reifman,et al. Support vector machines with selective kernel scaling for protein classification and identification of key amino acid positions , 2002, Bioinform..
[45] S. Radford,et al. Crystal structure of monomeric human β-2-microglobulin reveals clues to its amyloidogenic properties , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[46] M. Hecht,et al. Rationally designed mutations convert de novo amyloid-like fibrils into monomeric β-sheet proteins , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[47] J. Richardson,et al. Natural β-sheet proteins use negative design to avoid edge-to-edge aggregation , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[48] Judith Klein-Seetharaman,et al. A Novel Method of Protein Secondary Structure Prediction Using Context Sensitive Vocabulary , 2003 .