Biology Reference
In-Depth Information
9. Hirschberg DS (1975) Linear space algorithm
for computing longest common subsequences.
Commun Assoc Comput Mach 18:341-343
10. Myers E, Miller W (1988) Optimal alignments
in linear space. CABIOS 4:11-17
11. Chao KM, Pearson WR, Miller W (1992)
Aligning two sequences within a specified diag-
onal band. Comput Appl Biosci 8(5):481-487
12. Chao KM, Hardison RC, Miller W (1993)
Constrained sequence alignment. Comput
Appl Biosci 55(3):503-524
13. Hirschberg DS (1997) Serial computations of
Lcvenshtein distances. In: Pattern matching
algorithms. Oxford University Press, New
York, pp 123-141
14. Huang X, Hardison RC, Miller W (1990) A
space-efficient algorithm for local similarities.
Comput Appl Biosci 6(4):373-381
15. Huang XQ, Miller W (1991) A time-efficient,
linear-space local similarity algorithm. Adv
Appl Math 12(3):337-357
16. Chao KM, Hardison RC, Miller W (1994)
Recent developments in linear-space alignment
methods: a survey. J Comput Biol 1:271-291
17. Spouge JL (1989) Speeding up dynamic pro-
gramming algorithms for finding optimal lat-
tice
25. Hohwald H, Thayer I, Korf RE (2003) Com-
paring best-first search and dynamic program-
ming for optimal multiple sequence alignment.
In: Proceedings of the 18th international joint
conference on artificial intelligence, IJCAI'03.
Morgan Kaufmann Publishers, San Francisco,
pp 1239-1245
26. Korf RE, Zhan W (2000) Divide-and-conquer
frontier search applied to optimal sequence
alignment. In: Proceedings of the 7th confer-
ence on artificial intelligence (AAAI-00) and of
the 12th conference on innovative applications
of artificial intelligence (IAAI-00). AAA1 Press,
Cambridge, MA, pp 910-916
27. Lipman DJ, Altschul SF, Kececioglu JD (1989)
A tool for multiple sequence alignment. Proc
Natl Acad Sci USA 86:4412-4415
28. Stoye J, Perrey SW, Dress AWM (1997)
Improving the divide- and-conquer approach
to sum-of-pairs multiple sequence alignment.
Appl Math Lett 10(2):67-73
29. Sobel E, Martinez HM (1986) A multiple
sequence alignment program. Nucleic Acids
Res 14(1):363-374
30. Morgenstern B, Frech K, Dress A, Werner T
(1998) Dialign: finding local similarities by
multiple sequence alignment. Bioinformatics
14(3):290-294
31. Thompson JD, Higgins DG, Gibson TJ
(1994) Clustal w: improving the sensitivity of
progressive multiple sequence alignment
through sequence weighting, position-specific
gap penalties and weight matrix choice.
Nucleic Acids Res 22:4673-4680
32. Notredame C, Higgins DG, Heringa J (2000)
T-coffee: a novel method for fast and accurate
multiple sequence alignment.
paths.
SIAM J Appl Math
49
(5):1552-1566
18. Korf RE (1985) Depth-first iterative-
deepening: an optimal admissible tree search.
Artif Intell 27(1):97-109
19. Ukkonen E (1985) Algorithms for approxi-
mate string matching. Inf Control 64:100-118
20. Lipman DJ, Pearson WR (1985) Rapid and
sensitive protein similarity searches. Science
227(4693):1435-1441
21. Pearson WR, Lipman DJ (1988) Improved
tools for biological sequence comparison.
Proc Natl Acad Sci USA 85(8):2444-2448
22. Altschul S, Gish W, Miller W, Myers E, Lipman
DJ (1990) Basic local alignment search tool. J
Mol Biol 215(3):403-410
23. Altschul S, Madden TL, Schaffer AA, Zhang J,
Zhang Z, Miller W, Lipman DJ (1997) Gapped
blast and psi-blast: a new generation of protein
database search programs. Nucleic Acids Res
25:3389-3402
24. Kielbasa SM, Wan R, Sato K, Horton P, FrithMC
(2011) Adaptive seeds tame genomic sequence
comparison. Genome Res 21(3):487-493
J Mol Biol
302:205-217
33. Edgar RC (2004) Muscle: multiple sequence
alignment with high accuracy
and high
throughput.
Nucleic
Acids
Res
32
(5):1792-1797
34. Katoh K, Misawa K, Kuma K, Miyata T (2002)
MAFFT: a novel method for rapid multiple
sequence alignment based on fast Fourier
transform. Nucleic Acids Res 30:3059-3066
35. Russell DJ, Otu HH, and Sayood K (2008)
Grammar-based distance in progressive multi-
ple sequence alignment. BMC Bioinformatics,
9:306
