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University of Waterloo

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Golod, Daniil.
The *k*-*best* *paths* in Hidden Markov Models. Algorithms and Applications to Transmembrane Protein Topology Recognition.

Degree: 2009, University of Waterloo

URL: http://hdl.handle.net/10012/4603

Traditional algorithms for hidden Markov model decoding seek to maximize
either the probability of a state path or the number of positions of a sequence
assigned to the correct state. These algorithms provide only a single answer and
in practice do not produce good results. The most mathematically sound of these
algorithms is the Viterbi algorithm, which returns the state path that has the
highest probability of generating a given sequence. Here, we explore an extension to
this algorithm that allows us to ﬁnd the k paths of highest probabilities. The naive
implementation of k best Viterbi paths is highly space-inefficient, so we adapt recent
work on the Viterbi algorithm for a single path to this domain. Out algorithm uses
much less memory than the naive approach. We then investigate the usefulness
of the k best Viterbi paths on the example of transmembrane protein topology
prediction. For membrane proteins, even simple path combination algorithms give
good explanations, and if we look at the paths we are combining, we can give a
sense of conﬁdence in the explanation as well. For proteins with two topologies,
the k best paths can give insight into both correct explanations of a sequence, a
feature lacking from traditional algorithms in this domain.

Subjects/Keywords: HMM; k-best paths; transmembrane topology

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APA (6^{th} Edition):

Golod, D. (2009). The k-best paths in Hidden Markov Models. Algorithms and Applications to Transmembrane Protein Topology Recognition. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/4603

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Golod, Daniil. “The k-best paths in Hidden Markov Models. Algorithms and Applications to Transmembrane Protein Topology Recognition.” 2009. Thesis, University of Waterloo. Accessed November 15, 2019. http://hdl.handle.net/10012/4603.

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Golod, Daniil. “The k-best paths in Hidden Markov Models. Algorithms and Applications to Transmembrane Protein Topology Recognition.” 2009. Web. 15 Nov 2019.

Vancouver:

Golod D. The k-best paths in Hidden Markov Models. Algorithms and Applications to Transmembrane Protein Topology Recognition. [Internet] [Thesis]. University of Waterloo; 2009. [cited 2019 Nov 15]. Available from: http://hdl.handle.net/10012/4603.

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Golod D. The k-best paths in Hidden Markov Models. Algorithms and Applications to Transmembrane Protein Topology Recognition. [Thesis]. University of Waterloo; 2009. Available from: http://hdl.handle.net/10012/4603

Not specified: Masters Thesis or Doctoral Dissertation