Improved model for statistical alignment

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Description

The statistical approach to molecular sequence evolution involves the stochastic modeling of the substitution, insertion and deletion processes. Substitution has been modeled in a reliable way for more than three decades by using finite Markov-processes. Insertion and deletion, however, seem to be more difficult to model, and thc recent approaches cannot acceptably deal with multiple insertions and deletions. A new method based on a generating function approach is introduced to describe the multiple insertion process. The presented algorithm computes the approximate joint probability of two sequences in 0(13) running time where 1 is the geometric mean of the sequence lengths.

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11 p.

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Miklos, I. & Toroczkai, Z. (Zoltan) January 1, 2001.

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Description

The statistical approach to molecular sequence evolution involves the stochastic modeling of the substitution, insertion and deletion processes. Substitution has been modeled in a reliable way for more than three decades by using finite Markov-processes. Insertion and deletion, however, seem to be more difficult to model, and thc recent approaches cannot acceptably deal with multiple insertions and deletions. A new method based on a generating function approach is introduced to describe the multiple insertion process. The presented algorithm computes the approximate joint probability of two sequences in 0(13) running time where 1 is the geometric mean of the sequence lengths.

Physical Description

11 p.

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  • Submitted to: 1st Workshop on Algorithmus in BioInformatics, BRICS, University of ASarhus, Denmark, August 28-31, 2001

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  • Report No.: LA-UR-01-3270
  • Grant Number: none
  • Office of Scientific & Technical Information Report Number: 975548
  • Archival Resource Key: ark:/67531/metadc933080

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Office of Scientific & Technical Information Technical Reports

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  • January 1, 2001

Added to The UNT Digital Library

  • Nov. 13, 2016, 7:26 p.m.

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  • Dec. 9, 2016, 11:41 p.m.

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Miklos, I. & Toroczkai, Z. (Zoltan). Improved model for statistical alignment, article, January 1, 2001; United States. (digital.library.unt.edu/ark:/67531/metadc933080/: accessed May 26, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.