Homology search with binary and trinary scoring matrices

International Journal of Bioinformatics Research and Applications

Volumn 2, Issue 2, 2006, Pages 119-131

  Smith, Scott F ^a,b,c  

^a Boise State University   (United States)

^b BOISE STATE UNIVERSITY   (United States)

^c IEEE   (United States)

Author keywords

Bit parallel algorithms; Database search; Homology; Protein similarity; Smith Waterman algorithm; Substitution matrices

Indexed keywords

ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; DATA BASE; MATHEMATICAL COMPUTING; PROTEIN DATA BANK; RECEIVER OPERATING CHARACTERISTIC; SCORING SYSTEM; SEQUENCE ANALYSIS; SEQUENCE HOMOLOGY;

EID: 33745819199     PISSN: 17445458     EISSN: 17445493     Source Type: Journal    
DOI: 10.1504/IJBRA.2006.009763     Document Type: Article

References (19)

1. Allison, L. and Dix, T. (1986) 'A bit-string longest-common-subsequence algorithm', Information Processing Letters, Vol. 23, pp.305-310.
2. Altschul, S., Gish, W., Miller, W., Myers, E. and Lipman. D. (1990) 'Basic local alignment search tool', Journal of Molecular Biology, Vol. 215, No. 3, pp.403-410.
3. Benson, D., Karsch-Mizrachi, I., Lipman, D., Ostell, J. and Wheeler, D. (2004) 'GenBank update', Nucleic Acids Research, Vol. 32, pp.D23-D26.
4. Berman, H., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T., Weissig, H., Shindyalov, I. and Bourne, P. (2000) 'The protein data bank', Nucleic Acids Research, Vol. 28, pp.235-242.
5. Branden, C. and Tooze, J. (1999) Introduction to Protein Structure, 2nd ed., Garland.
6. Brown, S. and Vranesic, Z. (2005) Fundamentals of Digital Logic with VHDL Design, 2nd ed., McGraw Hill.
7. Cameron, M., Williams, H. and Cannane, A. (2004) 'Improved gapped alignment in BLAST', IEEE Trans. Computational Biology and Bioinformatics, Vol. 1. pp. 116-129.
8. Chandonia, J., Hon, G., Walker, N., Lo Conte, L., Koehl, P., Levitt, M. and Brenner, S. (2004) 'The ASTRAL compendium in 2004', Nucleic Acids Research. Vol. 32. pp.D189-D192.
9. Chen, Z. (2003) 'Assessing sequence comparison methods with the average precision criterion', Bioinformatics, Vol. 19, No. 18, pp.2456-2460.
10. Crochemore, M., Iliopoulos, C., Pinzon, Y. and Reid, J. (2001) 'A fast and practical bit-vector algorithm for the longest common subsequence problem', Information Processing Letters, Vol. 80, pp.279-285.
11. Dayhoff, M., Schwartz, R. and Orcutt, B. (1978) 'A model of evolutionary change in proteins', Atlas of Protein Sequence and Structure, Vol. 5, pp.345-358.
12. Durbin, R., Eddy, S., Krogh, A. and Mitchison, G. (1998) Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids, Cambridge University Press, Cambridge.
13. Gotoh, O. (1982) 'An improved algorithm for matching biological sequences', Journal of Molecular Biology. Vol. 162, pp.705-708.
14. Gribskov, M. and Robinson, N. (1996) 'Use of receiver operating characteristic (ROC) analysis to evaluate sequence matching'. Computers and Chemistry, Vol. 20, pp.25-33.
15. Henikoff, S. and Henikoff, J. (1992) 'Amino acid substitution matrices from protein blocks', Proceedings of the National Academy of Sciences, Washington DC, Vol. 89, No. 22, pp.10915-10919.
16. Murzin, A., Brenner, S., Hubbard, T. and Chothia, C. (1995) 'SCOP: a structural classification of proteins database for the investigation of sequences and structures', Journal of Molecular Biology, Vol. 247, No. 4, pp.536-540.
17. Myers, G. (1999) 'A fast bit-vector algorithm for approximate string matching based on dynamic programming', Journal of the ACM, Vol. 46, pp.395-415.
18. Pearson, W. and Lipman, D. (1998) 'Improved tools for biological sequence comparisons', Proceedings of the National Academy of Sciences, Washington DC, Vol. 85, No. 8, pp.2444-2448.
19. Smith, T. and Waterman, M. (1981) 'Identification of common molecular subsequences', Journal of Molecular Biology, Vol. 147, No. 1, pp.195-197.