A new statistical framework to assess structural alignment quality using information compression

Bioinformatics

Volumn 30, Issue 17, 2014, Pages

  Collier, James H ^a   Allison, Lloyd ^a   Lesk, Arthur M ^b   De La Banda, Maria Garcia ^a   Konagurthu, Arun S ^a  

^a MONASH UNIVERSITY   (Australia)

^b PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; INFORMATION PROCESSING; STATISTICAL ANALYSIS; STRUCTURAL HOMOLOGY;

ALGORITHMS; DATA COMPRESSION; DATA INTERPRETATION, STATISTICAL; STRUCTURAL HOMOLOGY, PROTEIN;

EID: 84907027200     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btu460     Document Type: Conference Paper

References (21)

1. Allison, L. et al. (1992) Finite-state models in the alignment of macromolecules. J. Mol. Evol., 35, 77-89.
2. Altschul, S.F. (1991) Amino acid substitution matrices from an information theoretic perspective. J. Mol. Biol., 219, 555-565.
3. Fisher, R. (1953) Dispersion on a sphere. Proc. R. Soc. Lond. A, 217, 295-305.
4. Hasegawa, H. and Holm, L. (2009) Advances and pitfalls of protein structural alignment. Curr. Opin. Struct. Biol., 19, 341-348.
5. Irving, J.A. et al. (2001) Protein structural alignments and functional genomics. Proteins, 42, 378-382.
6. Karlin, S. and Altschul, S.F. (1990) Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes. Proc. Natl Acad. Sci. USA, 87, 2264-2268.
7. Kolmogorov, A. (1965) Three approaches to the quantitative definition of information. Probl. Inform. Transm., 1, 1-7.
8. Kolodny, R. et al. (2005) Comprehensive evaluation of protein structure alignment methods: scoring by geometric measures. J. Mol. Biol., 346, 1173-1188.
9. Konagurthu, A.S. et al. (2006) MUSTANG: a multiple structural alignment algorithm. Proteins, 64, 559-574.
10. Konagurthu, A.S. et al. (2012) Minimum message length inference of secondary structure from protein coordinate data. Bioinformatics, 28, i97-i105.
11. Konagurthu, A.S. et al. (2014) On sufficient statistics of least-squares superposition of vector sets. RECOMB, 8394, 144-159.
12. Lo Conte, L. et al. (2000) SCOP: a structural classification of proteins database. Nucleic Acids Res., 28, 257-259.
13. Mardia, K. and Jupp, P. (1999) Directional Statistics. Probability and Statistics. Wiley, Chichester, England.
14. Shannon, C.E. (1948) A mathematical theory of communication. Bell Syst. Techn. J., 27, 379-423.
15. Sippl, M.J. and Wiederstein, M. (2008) A note on difficult structure alignment problems. Bioinformatics, 24, 426-427.
16. Slater, A. et al. (2013) Towards the deveopment of standardized methods for comparison, ranking and evaluation of structure alignments. Bioinformatics, 29, 47-53.
17. Solomonoff, R. (1960) A preliminary report on a general theory of inductive inference. In: Report V-131. Zator, Cambridge, MA.
18. Wallace, C.S. and Boulton, D.M. (1968) An information measure for classification. Comp. J., 11, 185-194.
19. Wallace, C.S. and Boulton, D.M. (1969) The information content of a multistate distribution. J. Theor. Biol., 23, 269-278.
20. Wallace, C.S. and Patrick, J. (1993) Coding decision trees. Mach. Learn., 11, 7-22.
21. Zu-Kang, F. and Sippl, M. (1996) Optimum superimposition of protein structures: ambiguities and implications. Fold. Des., 1, 123-132.