A Bayesian network model for protein fold and remote homologue recognition
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[1] M. O. Dayhoff,et al. Atlas of protein sequence and structure , 1965 .
[2] M. O. Dayhoff,et al. 22 A Model of Evolutionary Change in Proteins , 1978 .
[3] W. Kabsch,et al. Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features , 1983, Biopolymers.
[4] A. D. McLachlan,et al. Profile analysis: detection of distantly related proteins. , 1987, Proceedings of the National Academy of Sciences of the United States of America.
[5] David J. Spiegelhalter,et al. Local computations with probabilities on graphical structures and their application to expert systems , 1990 .
[6] Martin Vingron,et al. A fast and sensitive multiple sequence alignment algorithm , 1989, Comput. Appl. Biosci..
[7] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[8] M. Sippl. Calculation of conformational ensembles from potentials of mean force. An approach to the knowledge-based prediction of local structures in globular proteins. , 1990, Journal of molecular biology.
[9] C. Sander,et al. Database of homology‐derived protein structures and the structural meaning of sequence alignment , 1991, Proteins.
[10] D. Eisenberg,et al. A method to identify protein sequences that fold into a known three-dimensional structure. , 1991, Science.
[11] M. Sippl,et al. Detection of native‐like models for amino acid sequences of unknown three‐dimensional structure in a data base of known protein conformations , 1992, Proteins.
[12] Bernhard E. Boser,et al. A training algorithm for optimal margin classifiers , 1992, COLT '92.
[13] D. T. Jones,et al. A new approach to protein fold recognition , 1992, Nature.
[14] S. Bryant,et al. An empirical energy function for threading protein sequence through the folding motif , 1993, Proteins.
[15] B. Rost,et al. Prediction of protein secondary structure at better than 70% accuracy. , 1993, Journal of molecular biology.
[16] C. Sander,et al. The FSSP database of structurally aligned protein fold families. , 1994, Nucleic acids research.
[17] B. Rost,et al. Conservation and prediction of solvent accessibility in protein families , 1994, Proteins.
[18] D. Haussler,et al. Hidden Markov models in computational biology. Applications to protein modeling. , 1993, Journal of molecular biology.
[19] J. Thompson,et al. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. , 1994, Nucleic acids research.
[20] Collin M. Stultz,et al. Protein classification by stochastic modeling and optimal filtering of amino-acid sequences. , 1994, Mathematical Biosciences.
[21] S. Bryant,et al. Threading a database of protein cores , 1995, Proteins.
[22] A G Murzin,et al. SCOP: a structural classification of proteins database for the investigation of sequences and structures. , 1995, Journal of molecular biology.
[23] C. Hodgman,et al. Reported sequence homology between Alzheimer amyloid770 and the MRC OX-2 antigen does not predict function , 1995, Brain Research Bulletin.
[24] A. Godzik,et al. Are proteins ideal mixtures of amino acids? Analysis of energy parameter sets , 1995, Protein science : a publication of the Protein Society.
[25] Burkhard Rost,et al. TOPITS: Threading One-Dimensional Predictions Into Three-Dimensional Structures , 1995, ISMB.
[26] Finn Verner Jensen,et al. Introduction to Bayesian Networks , 2008, Innovations in Bayesian Networks.
[27] David C. Jones,et al. Combining protein evolution and secondary structure. , 1996, Molecular biology and evolution.
[28] D. Fischer,et al. Protein fold recognition using sequence‐derived predictions , 1996, Protein science : a publication of the Protein Society.
[29] G. Barton,et al. Protein fold recognition by mapping predicted secondary structures. , 1996, Journal of molecular biology.
[30] Thomas L. Madden,et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. , 1997, Nucleic acids research.
[31] D. Fischer,et al. Assigning folds to the proteins encoded by the genome of Mycoplasma genitalium. , 1997, Proceedings of the National Academy of Sciences of the United States of America.
[32] A. Godzik,et al. Similarities and differences between nonhomologous proteins with similar folds: evaluation of threading strategies. , 1997, Folding & design.
[33] M. Sternberg,et al. Recognition of analogous and homologous protein folds: analysis of sequence and structure conservation. , 1997, Journal of molecular biology.
[34] B. Rost,et al. Protein fold recognition by prediction-based threading. , 1997, Journal of molecular biology.
[35] J. Garnier,et al. Fold recognition using predicted secondary structure sequences and hidden Markov models of protein folds , 1997, Proteins.
[36] C Venclovas,et al. Numerical criteria for the evaluation of ab initio predictions of protein structure , 1997, Proteins.
[37] C Sander,et al. Predicting protein structure using hidden Markov models , 1997, Proteins.
[38] Michael I. Jordan,et al. Probabilistic Independence Networks for Hidden Markov Probability Models , 1997, Neural Computation.
[39] M Levitt,et al. Competitive assessment of protein fold recognition and alignment accuracy , 1997, Proteins.
[40] Temple F. Smith,et al. The challenges of genome sequence annotation or “The devil is in the details” , 1997, Nature Biotechnology.
[41] Simon Kasif,et al. Computational methods in molecular biology , 1998 .
[42] Temple F. Smith,et al. A homology identification method that combines protein sequence and structure information , 1998, Protein science : a publication of the Protein Society.
[43] C. Chothia,et al. Structural assignments to the Mycoplasma genitalium proteins show extensive gene duplications and domain rearrangements. , 1998, Proceedings of the National Academy of Sciences of the United States of America.
[44] P E Bourne,et al. Protein structure alignment by incremental combinatorial extension (CE) of the optimal path. , 1998, Protein engineering.
[45] A. Godzik,et al. Fold and function predictions for Mycoplasma genitalium proteins. , 1998, Folding & design.
[46] Zoubin Ghahramani,et al. A Bayesian network approach to protein fold recognition , 1998 .
[47] Sean R. Eddy,et al. Profile hidden Markov models , 1998, Bioinform..
[48] C. Chothia,et al. Assessing sequence comparison methods with reliable structurally identified distant evolutionary relationships. , 1998, Proceedings of the National Academy of Sciences of the United States of America.
[49] R. Lathrop,et al. A Bayes-optimal probability theory that uni? es protein sequence-structure recognition and alignment , 1998 .
[50] D. Haussler,et al. Sequence comparisons using multiple sequences detect three times as many remote homologues as pairwise methods. , 1998, Journal of molecular biology.
[51] Temple F. Smith,et al. A Bayes-optimal sequence-structure theory that unifies protein sequence-structure recognition and alignment , 1998, Bulletin of mathematical biology.
[52] Temple F. Smith,et al. Analysis and algorithms for protein sequence–structure alignment , 1998 .
[53] R. Durbin,et al. Biological sequence analysis: Background on probability , 1998 .
[54] A. Elofsson,et al. Hidden Markov models that use predicted secondary structures for fold recognition , 1999, Proteins.
[55] David Haussler,et al. Using the Fisher Kernel Method to Detect Remote Protein Homologies , 1999, ISMB.
[56] A. Sali,et al. Structural genomics: beyond the Human Genome Project , 1999, Nature Genetics.
[57] M. Sternberg,et al. Benchmarking PSI-BLAST in genome annotation. , 1999, Journal of molecular biology.
[58] David C. Jones,et al. GenTHREADER: an efficient and reliable protein fold recognition method for genomic sequences. , 1999, Journal of molecular biology.
[59] Michael I. Jordan,et al. Probabilistic Networks and Expert Systems , 1999 .
[60] A. Godzik,et al. Functional insights from structural predictions: Analysis of the Escherichia coli genome , 2008, Protein science : a publication of the Protein Society.
[61] G J Barton,et al. Application of multiple sequence alignment profiles to improve protein secondary structure prediction , 2000, Proteins.
[62] Temple F. Smith,et al. Protein fold recognition by total alignment probability , 2000, Proteins.
[63] Nello Cristianini,et al. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .
[64] Pierre Baldi,et al. Assessing the accuracy of prediction algorithms for classification: an overview , 2000, Bioinform..
[65] Patrice Koehl,et al. The ASTRAL compendium for protein structure and sequence analysis , 2000, Nucleic Acids Res..
[66] Zoubin Ghahramani,et al. An Introduction to Hidden Markov Models and Bayesian Networks , 2001, Int. J. Pattern Recognit. Artif. Intell..
[67] Koby Crammer,et al. On the Learnability and Design of Output Codes for Multiclass Problems , 2002, Machine Learning.