HHsvm: Fast and accurate classification of profile-profile matches identified by HHsearch

Bioinformatics

Volumn 25, Issue 23, 2009, Pages 3071-3076

  Dlakić, Mensur ^a  

^a MONTANA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PROTEIN;

ARTICLE; BIOLOGY; CHEMISTRY; COMPUTER PROGRAM; METHODOLOGY; PROTEIN DATABASE; PROTEIN TERTIARY STRUCTURE; SEQUENCE HOMOLOGY;

COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; PROTEIN STRUCTURE, TERTIARY; PROTEINS; SEQUENCE HOMOLOGY, AMINO ACID; SOFTWARE;

EID: 75949107791     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btp555     Document Type: Article

References (31)

1. Altschul, S.F. et al. (1990) Basic local alignment search tool. J. Mol. Biol., 215, 403-410.
2. Altschul, S.F. et al. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res., 25, 3389-3402.
3. Andreeva, A. et al. (2008) Data growth and its impact on the SCOP database: new developments. Nucleic Acids Res., 36, D419-D425.
4. Aravind, L. et al. (2000) Holliday junction resolvases and related nucleases: identification of new families, phyletic distribution and evolutionary trajectories. Nucleic Acids Res., 28, 3417-3432.
5. Brenner, S.E. et al. (1998) Assessing sequence comparison methods with reliable structurally identified distant evolutionary relationships. Proc. Natl Acad. Sci. USA, 95, 6073-6078.
6. Chang, C. and Lin, C. (2001) LIBSVM: a library for support vector machines. http://www.csie.ntu.edu.tw/~cjlin/libsvm.
7. Cheng, H. et al. (2008) Discrimination between distant homologs and structural analogs: lessons from manually constructed, reliable data sets. J. Mol. Biol., 377, 1265-1278.
8. Eddy, S.R. (1998) Profile hidden Markov models. Bioinformatics, 14, 755-763.
9. Finn, R.D. et al. (2008) The Pfam protein families database. Nucleic Acids Res., 36, D281-D288.
10. Fischer, J.D. et al. (2008) Prediction of protein functional residues from sequence by probability density estimation. Bioinformatics, 24, 613-620.
11. Ginalski, K. et al. (2004) Detecting distant homology with Meta-BASIC. Nucleic Acids Res., 32, W576-W581.
12. Jones, D.T. (1999) Protein secondary structure prediction based on position-specific scoring matrices. J. Mol. Biol., 292, 195-202.
13. Karplus, K. et al. (1998) Hidden Markov models for detecting remote protein homologies. Bioinformatics, 14, 846-856.
14. Karplus, K. et al. (2003) Combining local-structure, fold-recognition, and new fold methods for protein structure prediction. Proteins, 53(Suppl. 6), 491-496.
15. Knizewski, L. et al. (2007) Realm of PD-(D/E)XK nuclease superfamily revisited: detection of novel families with modified transitive meta profile searches. BMC Struct. Biol., 7, 40.
16. Lin, H.-T. and Li, L. (2008) Support vector machinery for infinite ensemble learning. J. Mach. Learn. Res., 9, 285-312.
17. Madera, M. and Gough, J. (2002) A comparison of profile hidden Markov model procedures for remote homology detection. Nucleic Acids Res., 30, 4321-4328.
18. Orlowski, J. and Bujnicki, J.M. (2008) Structural and evolutionary classification of Type II restriction enzymes based on theoretical and experimental analyses. NucleicAcids Res., 36, 3552-3569.
19. Park, J. et al. (1998) Sequence comparisons using multiple sequences detect three times as many remote homologues as pairwise methods. J. Mol. Biol., 284, 1201-1210.
20. Pearson, W.R. and Lipman, D.J. (1988) Improved tools for biological sequence comparison, Proc. Natl. Acad. Sci. USA, 85, 2444-2448.
21. Platt, J. (2000) Probabilities for SV machines. In Bartlett, P.S. et al. (ed) Advances in Large Margin Classifiers. MIT Press, Cambridge, MA, pp. 61-74.
22. Reid, A.J. et al. (2007) Methods of remote homology detection can be combined to increase coverage by 10% in the midnight zone. Bioinformatics, 23, 2353-2360.
23. Rost, B. (1999) Twilight zone of protein sequence alignments. Protein Eng., 12, 85-94.
24. Sadreyev, R. and Grishin, N. (2003)COMPASS: a tool for comparison of multiple protein alignments with assessment of statistical significance. J. Mol. Biol., 326, 317-336.
25. Schneider, T.D. and Stephens, R.M. (1990) Sequence logos: a new way to display consensus sequences. Nucleic Acids Res., 18, 6097-6100.
26. Schuster-Bockler, B. and Bateman, A. (2005) Visualizing profile-profile alignment: pairwise HMM logos. Bioinformatics, 21, 2912-2913.
27. Shah, A.R. et al. (2008) SVM-HUSTLE-an iterative semi-supervised machine learning approach for pairwise protein remote homology detection. Bioinformatics, 24, 783-790.
28. Söding, J. (2005) Protein homology detection by HMM-HMM comparison. Bioinformatics, 21, 951-960.
29. Söding, J. et al. (2005) The HHpred interactive server for protein homology detection and structure prediction. Nucleic Acids Res., 33, W244-W248.
30. Vapnik, V.N. (1995) The Nature of Statistical Learning Theory. Springer, New York.
31. Yona, G. and Levitt, M. (2002) Within the twilight zone: a sensitive profile-profile comparison tool based on information theory. J. Mol. Biol., 315, 1257-1275.