A Bayesian network model for protein fold and remote homologue recognition

Bioinformatics

Volumn 18, Issue 6, 2002, Pages 788-801

  Raval, A ^a   Ghahramani, Z ^b   Wild, D L ^a  

^a KECK GRADUATE INSTITUTE   (United States)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID;

AMINO ACID SEQUENCE; ANALYTICAL ERROR; ARTICLE; BAYES THEOREM; CLASSIFICATION; COMPUTER GRAPHICS; CONTROLLED STUDY; MOLECULAR RECOGNITION; PREDICTION; PRIORITY JOURNAL; PROBABILITY; PROTEIN FAMILY; PROTEIN FOLDING; PROTEIN SECONDARY STRUCTURE; SEQUENCE DATABASE; SEQUENCE HOMOLOGY; THEORY; TRAINING; VALIDATION PROCESS;

EID: 0036300562     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/18.6.788     Document Type: Article

References (64)

1. Gapped BLAST and PSI-BLAST: A new generation of protein database search programs
2. Assessing the accuracy of prediction algorithms for classification: An overview
3. Protein fold recognition by total alignment probability
4. A training algorithm for optimal margin classifiers
5. A method to identify protein sequences that fold into a known three-dimensional structure
6. Assessing sequence comparison methods with reliable structurally identified distant evolutionary relationships
7. The ASTRAL compendium for protein structure and sequence analysis
8. An empirical energy function for threading protein sequence through the folding motif
9. Structural genomics: Beyond the Human Genome Project
10. Probabilistic Networks and Expert Systems
11. On the learnability and design of output codes for multiclass problems
12. Support Vector Machines and Other Kernel-Based Learning Methods
13. Application of multiple sequence alignment profiles to improve secondary structure prediction
14. A model of evolutionary change in proteins
15. Fold recognition using predicted secondary structure and hidden Markov models of protein folds
16. Biological Sequence Analysis
17. Profile hidden Markov models
18. Protein fold recognition using sequence-derived predictions
19. Assigning folds to the proteins encoded by the genome of Mycoplasma genitalium
20. An introduction to hidden Markov models and Bayesian networks
21. Are proteins ideal mixtures of amino acids? Analysis of energy parameter sets
22. Profile analysis: Detection of distantly related proteins
23. Hidden Markov models that use predicted secondary structures for fold recognition
24. The FSSP database of structurally aligned protein fold families
25. Using the Fisher kernel method to detect remote protein homologies
26. Introduction to Bayesian Networks
27. A new approach to protein fold recognition
28. GenTHREADER: An efficient and reliable protein fold recognition method for genomic sequences
29. Dictionary of protein secondary structure: Pattern recognition of hydrogen-bonded and geometrical features
30. Predicting protein structure using hidden Markov models
31. Hidden Markov models in computational biology-applications to protein modelling
32. Analysis and algorithms for protein sequence-structure alignment
33. A Bayes-optimal probability theory that unifies protein sequence-structure recognition and alignment
34. Local computations with probabilities on graphical structures and their application to expert systems
35. Competitive assessment of protein fold recognition and alignment accuracy
36. Threading a database of protein cores
37. Bench-marking PSI-BLAST in Genome Annotation
38. SCOP: A structural classification of proteins database for the investigation of sequences and structures
39. Sequence comparisons using multiple sequences detect three times as many remote homologues as pairwise methods
40. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
41. Reported sequence homology between Alzheimer amyloid-770 and the MRC OX-2 antigen does not predict homology
42. Prediction of protein secondary structure at better than 70% accuracy
43. Conservation and prediction of solvent accessibility in protein families
44. TOPITS: Threading one-dimensional predictions into three-dimensional structures
45. Protein fold recognition by prediction-based threading
46. Protein fold recognition by mapping predicted secondary structures
47. Recognition of analogous and homologous protein folds: Analysis of sequence and structure conservation
48. Fold and function predictions for Mycoplasma genitalium proteins
49. Functional insights from structure predictions: Analysis of the Escherichia coli genome
50. Database of homology-derived protein structures and the structural meaning of sequence alignment
51. Protein structure alignment by incremental combinatorial extension (CE) of the optimal path
52. Calculation of conformational ensembles from potentials of mean force
53. Detection of native-like models for amino acid sequences of unknown three-dimensional structure in a data base of known protein conformations
54. The challenges of genome sequence annotation or 'the devil is in the details'
55. Probabilistic independence networks for hidden Markov probability models
56. Structural assignments to the Mycoplasma genitalium proteins show extensive gene duplications and domain rearrangements
57. CLUSTAL W: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice
58. Combining protein evolution and secondary structure
59. A fast and sensitive mutiple sequence alignment algorithm
60. Protein classification by stochastic modeling and optimal filtering of amino acid sequences
61. A Bayesian network approach to protein fold recognition
62. A homology identification method that combines protein sequence and structure information
63. Numerical criteria for the evaluation of ab initio predictions of protein structure
64. Similarities and differences between non-homologous proteins with similar folds: Evaluation of threading strategies