Variations on probabilistic suffix trees: Statistical modeling and prediction of protein families

Bioinformatics

Volumn 17, Issue 1, 2001, Pages 23-43

  Bejerano, Gill ^a   Yona, Golan ^b,c  

^a HEBREW UNIVERSITY OF JERUSALEM   (Israel)

^b STANFORD UNIVERSITY   (United States)

^c Department of Computer Science and School of Operations Research and Information Engineering   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID; PROTEIN;

ALGORITHM; AMINO ACID ANALYSIS; AMINO ACID SEQUENCE; AMINO ACID SUBSTITUTION; ANALYTIC METHOD; ARTICLE; AUTOANALYSIS; CLASSIFICATION; DATA BASE; EVALUATION; INTERMETHOD COMPARISON; MEDICAL INFORMATION; PERFORMANCE; PREDICTION; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN DOMAIN; PROTEIN FAMILY; SATISFACTION; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL;

EID: 0035109647     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/17.1.23     Document Type: Article

References (46)

1. On the computational complexity of approximating distributions by probability automata
2. Amino acid substitution matrices from an information theoretic perspective
3. Gapped BLAST and PSI-BLAST: A new generation of protein database search programs
4. Optimal amnestic probabilistic automata or how to learn and classify proteins in linear time and space
5. PRINTS prepares for the new millennium
6. The value of prior knowledge in discovering motifs with MEME
7. The SWISS-PROT protein sequence data bank and its supplement TrEMBL in 1999
8. Model building by comparison at CASP3: Using expert knowledge and computer automation
9. Pfam 3.1: 1313 multiple alignments and profile HMMs match the majority of proteins
10. Recent improvements of the ProDom database of protein domain families
11. Maximum likelihood from incomplete data via the EM algorithm
12. HMMER user's guide: Biological sequence analysis using profile hidden Markov models
13. Contribution of cotranslational folding to the rate of formation of native prote in structure
14. Circular permutation of granulocyte colony-stimulating factor
15. Inference and minimization of hidden Markov chains
16. Correlated mutations amongst the external residues of G-protein coupled receptors
17. Automated protein sequence database classification I. Integration of copositional similarity search, local similarity search and multiple sequence alignment II. Delineation of domain boundaries from sequence similarity
18. Profile analysis: Detection of distantly related proteins
19. Self-organizing hierarchic networks for pattern recognition in protein sequence
20. Amino acid substitution matrices from protein blocks
21. Using substitution probabilities to improve position-specific scoring matrices
22. New features of the blocks database serves
23. Random circular permutation of DsbA reveals segments that are essential for protein folding and stability
24. Using CLUSTAL for multiple sequence alignments
25. The PROSITE database, its status in 1999
26. SAM: Sequence alignment and modeling software system
27. Finding flexible patterns in unaligned protein sequences
28. Cotranslational folding of proteins
29. Hidden Markov models in computational biology: Application to protein modeling
30. Detecting subtle sequence signals: A Gibbs sampling strategy for multiple alignment
31. Highly specific protein sequence motifs for genome analysis
32. Detecting patterns in protein sequences
33. Folding of circular and permuted chymotrypsin inhibitor 2: Retention of the folding nucleus
34. Correlated mutations contain information about protein-protein interaction
35. Comparison of methods for searching protein sequence databases
36. SMART: Identification and annotation of domains from signaling and extracellular protein sequences
37. Lattice neural network minimization. Application of neural network optimization for locating the global-minimum conformations of proteins
38. Stochastic complexity in statistical inquiry
39. The power of amnesia: Learning probabilistic automata with variable memory length
40. Handling context-sensitivity in protein structures using graph theory: Bonafide prediction
41. Finding sequence motifs in groups of functionally related proteins
42. Searching for common sequence patterns among distantly related proteins
43. Foldability of barnase mutants obtained by permutation of modules or secondary structure units
44. ProtoMap: Automatic classification of protein sequences, a hierarchy of protein families, and local maps of the protein space