Investigation and prediction of the severity of p53 mutants using parameters from structural calculations
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[1] Ronald Eugene Shaffer,et al. Multi‐ and Megavariate Data Analysis. Principles and Applications, I. Eriksson, E. Johansson, N. Kettaneh‐Wold and S. Wold, Umetrics Academy, Umeå, 2001, ISBN 91‐973730‐1‐X, 533pp. , 2002 .
[2] W. Kabsch,et al. Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features , 1983, Biopolymers.
[3] J. Bond,et al. Detailed computational study of p53 and p16: using evolutionary sequence analysis and disease-associated mutations to predict the functional consequences of allelic variants , 2003, Oncogene.
[4] P. Meisel. Margaret O. Dayhoff: Atlas of Protein Sequence and Structure 1969 (Volume 4) XXIV u. 361 S., 21 Ausklapptafeln, 68 Abb. und zahlreiche Tabellen. National Biomedical Research Foundation, Silver Spring/Maryland 1969. Preis $ 12,50 , 1971 .
[5] Ruben Abagyan,et al. ICM—A new method for protein modeling and design: Applications to docking and structure prediction from the distorted native conformation , 1994, J. Comput. Chem..
[6] H. Scheraga,et al. Energy parameters in polypeptides. 10. Improved geometrical parameters and nonbonded interactions for use in the ECEPP/3 algorithm, with application to proline-containing peptides , 1994 .
[7] András Fiser,et al. Modeling mutations in protein structures , 2007, Protein science : a publication of the Protein Society.
[8] S. Chanock,et al. The devil is in the DNA , 2007, Nature Genetics.
[9] B. Matthews. Comparison of the predicted and observed secondary structure of T4 phage lysozyme. , 1975, Biochimica et biophysica acta.
[10] S. Henikoff,et al. Accounting for human polymorphisms predicted to affect protein function. , 2002, Genome research.
[11] Rodrigo Lopez,et al. Multiple sequence alignment with the Clustal series of programs , 2003, Nucleic Acids Res..
[12] S. Henikoff,et al. Predicting deleterious amino acid substitutions. , 2001, Genome research.
[13] D. Chasman,et al. Predicting the functional consequences of non-synonymous single nucleotide polymorphisms: structure-based assessment of amino acid variation. , 2001, Journal of molecular biology.
[14] K A Schulman,et al. Mathematical Models in Decision Analysis , 1997, Infection Control & Hospital Epidemiology.
[15] G. Parmigiani,et al. The Consensus Coding Sequences of Human Breast and Colorectal Cancers , 2006, Science.
[16] Shunsuke Kato,et al. Computational approaches for predicting the biological effect of p53 missense mutations: a comparison of three sequence analysis based methods , 2006, Nucleic acids research.
[17] M. O. Dayhoff,et al. Atlas of protein sequence and structure , 1965 .
[18] R. Abagyan,et al. Biased probability Monte Carlo conformational searches and electrostatic calculations for peptides and proteins. , 1994, Journal of molecular biology.
[19] J. Rodgers,et al. Thirteen ways to look at the correlation coefficient , 1988 .
[20] E. Birney,et al. Patterns of somatic mutation in human cancer genomes , 2007, Nature.
[21] S. Kato,et al. Understanding the function–structure and function–mutation relationships of p53 tumor suppressor protein by high-resolution missense mutation analysis , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[22] C Béroud,et al. p53 Website and analysis of p53 gene mutations in human cancer: Forging a link between epidemiology and carcinogenesis , 2000, Human mutation.
[23] Andreas Daffertshofer,et al. PCA in studying coordination and variability: a tutorial. , 2004, Clinical biomechanics.
[24] Piero Fariselli,et al. Predicting protein stability changes from sequences using support vector machines , 2005, ECCB/JBI.
[25] A. Zharkikh,et al. Comprehensive statistical study of 452 BRCA1 missense substitutions with classification of eight recurrent substitutions as neutral , 2005, Journal of Medical Genetics.
[26] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[27] B. Persson,et al. Molecular model of human CYP21 based on mammalian CYP2C5: structural features correlate with clinical severity of mutations causing congenital adrenal hyperplasia. , 2006, Molecular endocrinology.
[28] D C Richardson,et al. The kinemage: A tool for scientific communication , 1992, Protein science : a publication of the Protein Society.
[29] Alison L. Cuff,et al. Integrating mutation data and structural analysis of the TP53 tumor‐suppressor protein , 2002, Human mutation.
[30] J. Trent,et al. WAF1, a potential mediator of p53 tumor suppression , 1993, Cell.
[31] M. Michael Gromiha,et al. CUPSAT: prediction of protein stability upon point mutations , 2006, Nucleic Acids Res..
[32] M. Tang,et al. Preferential Formation of Benzo[a]pyrene Adducts at Lung Cancer Mutational Hotspots in P53 , 1996, Science.
[33] P. Jeffrey,et al. Crystal structure of a p53 tumor suppressor-DNA complex: understanding tumorigenic mutations. , 1994, Science.
[34] Olivier Michielin,et al. Structural assessment of single amino acid mutations: application to TP53 function , 2006, Human mutation.
[35] Thierry Soussi,et al. Assessing TP53 status in human tumours to evaluate clinical outcome , 2001, Nature Reviews Cancer.
[36] M. Barenboim,et al. Statistical geometry approach to the study of functional effects of human nonsynonymous SNPs , 2005, Human mutation.
[37] R. Doolittle,et al. A simple method for displaying the hydropathic character of a protein. , 1982, Journal of molecular biology.
[38] E. Birney,et al. Patterns of somatic mutation in human cancer genomes , 2007, Nature.
[39] J. M. Zimmerman,et al. The characterization of amino acid sequences in proteins by statistical methods. , 1968, Journal of theoretical biology.
[40] J. Moult,et al. SNPs, protein structure, and disease , 2001, Human mutation.
[41] Yuelan Wang,et al. Prediction of functional nonsynonymous single nucleotide polymorphisms in human G-protein-coupled receptors , 2008, Journal of Human Genetics.
[42] L. Serrano,et al. Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations. , 2002, Journal of molecular biology.