Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

You searched for subject:(k best paths). One record found.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters


University of Waterloo

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

Degree: 2009, University of Waterloo

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

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th 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 (16th 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 (7th 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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.