Derived Distribution Points heuristic for fast pairwise statistical significance estimation

2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010

Volumn , Issue , 2010, Pages 312-321

  Agrawal, Ankit ^a   Choudhary, Alok ^a   Huang, Xiaoqiu ^b  

^a Northwestern University   (United States)

^b Iowa State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATABASE STATISTICAL SIGNIFICANCE; DISTRIBUTION POINTS; ESTIMATION PROCEDURES; PAIRWISE SEQUENCE ALIGNMENT; PAIRWISE STATISTICAL SIGNIFICANCE; RETRIEVAL ACCURACY; SEQUENCE PAIR; SPEED-UPS; STATISTICAL SIGNIFICANCE;

BIOINFORMATICS; ESTIMATION;

STATISTICS;

EID: 77958023962     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1854776.1854819     Document Type: Conference Paper

References (36)

1. A. Agrawal, V. Brendel, and X. Huang. Pairwise statistical significance versus database statistical significance for local alignment of protein sequences. In Bioinformatics Research and Applications, volume 4983 of LNCS(LNBI), pages 50-61. Springer Berlin/Heidelberg, 2008.
2. A. Agrawal, V. P. Brendel, and X. Huang. Pairwise Statistical Significance and Empirical Determination of Effective Gap Opening Penalties for Protein Local Sequence Alignment. International Journal of Computational Biology and Drug Design, 1(4):347-367, 2008.
3. A. Agrawal and X. Huang. Pairwise statistical significance of local sequence alignment using substitution matrices with sequence-pair-specific distance. In Proc. of Intl. Conf. on Information Technology, ICIT, pages 94-99, 2008.
4. A. Agrawal and X. Huang. Pairwise Statistical Significance of Local Sequence Alignment Using Multiple Parameter Sets and Empirical Justification of Parameter Set Change Penalty. BMC Bioinformatics, 10(Suppl 3):S1, 2009.
5. A. Agrawal and X. Huang. Pairwise statisticalsignificance of local sequence alignment using sequence-specific and position-specific substitution matrices. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2009. 25 Sept. 2009.
6. A. Agrawal and X. Huang. PSIBLAST PairwiseStatSig: reordering PSI-BLAST hits using pairwise statistical significance. Bioinformatics, 25(8):1082-1083, 2009.
7. A. Agrawal, S. Misra, D. Honbo, and A. Choudhary. Mpipairwisestatsig: Parallel pairwise statistical significance estimation of local sequence alignment. In ECMLS proceedings of HPDC 2010, 2010. to appear.
8. S. F. Altschul, M. S. Boguski, W. Gish, and J. C. Wootton. Issues in searching molecular sequence databases. Nature Genetics, 6(2):119-129, 1994.
9. S. F. Altschul and W. Gish. Local Alignment Statistics. Methods in Enzymology, 266:460-80, 1996.
10. S. F. Altschul, W. Gish, W. Miller, E. W. Myers, and D. J. Lipman. Basic Local Alignment Search Tool. Journal of Molecular Biology, 215(3):403-410, 1990.
11. S. F. Altschul, T. L. Madden, A. A. Schäffer, J. Zhang, Z. Zhang, W. Miller, and D. J. Lipman. Gapped BLAST and PSI-BLAST: A New Generation of Protein Database Search Programs. Nucleic Acids Research, 25(17):3389-3402, 1997.
12. S. R. Eddy. Maximum likelihood fitting of extreme value distributions. 1997. unpublished work.
13. D. Honbo, A. Agrawal, and A. Choudhary. Fpga-accelerated local sequence alignment for pairwise statistical significance estimation. In Proceedings of BIOCOMP 2010, 2010. to appear.
14. X. Huang and D. L. Brutlag. Dynamic Use of Multiple Parameter Sets in Sequence Alignment. Nucleic Acids Research, 35(2):678-686, 2007.
15. X. Huang and K.-M. Chao. A Generalized Global Alignment Algorithm. Bioinformatics, 19(2):228-233, 2003.
16. S. Karlin and S. F. Altschul. Methods for Assessing the Statistical Significance of Molecular Sequence Features by Using General Scoring Schemes. Proceedings of the National Academy of Sciences, USA, 87(6):2264-2268, 1990.
17. M. Li, B. Ma, D. Kisman, and J. Tromp. PatternHunter II: Highly Sensitive and Fast Homology Search. Journal of Bioinformatics and Computational Biology, 2(3):417-439, 2004. Early version in GIW 2003.
18. B. Ma, J. Tromp, and M. Li. PatternHunter: faster and more sensitive homology search. Bioinformatics, 18(3):440-445, 2002.
19. A. Y. Mitrophanov and M. Borodovsky. Statistical Significance in Biological Sequence Analysis. Briefings in Bioinformatics, 7(1):2-24, 2006.
20. R. Mott. Accurate Formula for P-values of Gapped Local Sequence and Profile Alignments. Journal of Molecular Biology, 300:649-659, 2000.
21. R. Mott. Alignment: Statistical Significance. Encyclopedia of Life Sciences, 2005. available at http://mrw.interscience.wiley.com/emrw/ 9780470015902/els/article/a0005264/current/abstract.
22. R. Olsen, R. Bundschuh, and T. Hwa. Rapid assessment of extremal statistics for gapped local alignment. In Proc. of the Seventh International Conference on Intelligent Systems for Molecular Biology, pages 211-222. AAAI Press, 1999.
23. C. A. Orengo, A. D. Michie, S. Jones, D. T. Jones, M. B. Swindells, and J. M. Thornton. CATH - A Hierarchic Classification of Protein Domain Structures. Structure, 28(1):1093-1108, 1997
24. M. Pagni and C. V. Jongeneel. Making Sense of Score Statistics for Sequence Alignments. Briefings in Bioinformatics, 2(1):51-67, 2001.
25. W. R. Pearson. Effective Protein Sequence Comparison. Methods in Enzymology, 266:227-259, 1996.
26. W. R. Pearson. Empirical Statistical Estimates for Sequence Similarity Searches. Journal of Molecular Biology, 276:71-84, 1998.
27. W. R. Pearson. Flexible Sequence Similarity Searching with the FASTA3 Program Package. Methods in Molecular Biology, 132:185-219, 2000.
28. W. R. Pearson and D. J. Lipman. Improved Tools for Biological Sequence Comparison. Proceedings of the National Academy of Sciences, USA, 85(8):2444-2448, 1988.
29. W. R. Pearson and T. C. Wood. Statistical Significance in Biological Sequence Comparison. In D. J. Balding, M. Bishop, and C. Cannings, editors, Handbook of Statistical Genetics, pages 39-66. Chichester, UK: Wiley, 2001.
30. J. Rocha, F. Rosselló, and J. Segura. Compression Ratios Based on the Universal Similarity Metric Still Yield Protein Distances far from CATH Distances. CoRR, abs/q-bio/0603007, 2006.
31. A. A. Schäffer, L. Aravind, T. L. Madden, S. Shavirin, J. L. Spouge, Y. I. Wolf, E. V. Koonin, and S. F. Altschul. Improving the Accuracy of PSI-BLAST Protein Database Searches with Composition-based Statistics and Other Refinements. Nucleic Acids Research, 29(14):2994-3005, 2001.
32. M. L. Sierk and W. R. Pearson. Sensitivity and Selectivity in Protein Structure Comparison. Protein Science, 13(3):773-785, 2004.
33. T. F. Smith and M. S. Waterman. Identification of Common Molecular Subsequences. Journal of Molecular Biology, 147(1):195-197, 1981.
34. M. S. Waterman and M. Vingron. Rapid and Accurate Estimates of Statistical Significance for Sequence Database Searches. Proceedings of the National Academy of Sciences, USA, 91(11):4625-4628, 1994.
35. Y.-K. Yu and S. F. Altschul. The construction of amino acid substitution matrices for the comparison of proteins with non-standard compositions. Bioinformatics, 21(7):902-911, 2005.
36. Y.-K. Yu, E. M. Gertz, R. Agarwala, A. A. Schäffer, and S. F. Altschul. Retrieval Accuracy, Statistical Significance and Compositional Similarity in Protein Sequence Database Searches. Nucleic Acids Research, 34(20):5966-5973, 2006.