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Multiple Sequence Alignment

This article provides an overview of multiple sequence alignment (MSA) methods, detailing the challenges and scoring techniques. It covers SP-score, MSA algorithms for three sequences, NP-Complete, and progressive alignment approach by Feng and Doolittle. Approximation algorithms and time complexities are also discussed.

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Multiple Sequence Alignment

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  1. Multiple Sequence Alignment Kun-Mao Chao (趙坤茂) Department of Computer Science and Information Engineering National Taiwan University, Taiwan WWW: http://www.csie.ntu.edu.tw/~kmchao

  2. MSA

  3. Multiple sequence alignment (MSA) • The multiple sequence alignment problem is to simultaneously align more than two sequences. Seq1: GCTC Seq2: AC Seq3: GATC GC-TC A---C G-ATC

  4. How to score an MSA? • Sum-of-Pairs (SP-score) GC-TC A---C Score + GC-TC A---C G-ATC GC-TC G-ATC Score Score = + A---C G-ATC Score

  5. Gaps

  6. MSA for three sequences • an O(n3) algorithm

  7. MSA for three sequences

  8. General MSA • For k sequences of length n: O(nk) • NP-Complete (Wang and Jiang) • The exact multiple alignment algorithms for many sequences are not feasible. • Some approximation algorithms are given.(e.g., 2- l/k for any fixed l by Bafna et al.)

  9. Progressive alignment • A heuristic approach proposed by Feng and Doolittle. • It iteratively merges the most similar pairs. • “Once a gap, always a gap” The time for progressive alignment in most cases is roughly the order of the time for computing all pairwise alignment, i.e., O(k2n2). A B C D E

  10. Guiding Trees

  11. Aligning Alignments

  12. Gaps

  13. Quasi-Gaps

  14. Gap Starts & Gap Ends

  15. Gaps

  16. Nine Ways In

  17. D[i, j]

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