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Protein secondary structure prediction using amino acid regularities
Dissertation (MEng)--University of Pretoria, 2009.
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| Format: | Thesis |
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University of Pretoria
2013
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| _version_ | 1867613526013509632 |
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| access_status_str | Open Access |
| author2 | Barnard, E. |
| author_browse | Barnard, E. |
| author_facet | Barnard, E. |
| collection | Thesis |
| dc_rights_str_mv | ©University of Pretoria 2008 E1196/ |
| description | Dissertation (MEng)--University of Pretoria, 2009. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/24612 |
| institution | University of Pretoria (South Africa) |
| last_indexed | 2026-06-10T12:37:32.711Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2013 |
| publishDateRange | 2013 |
| publishDateSort | 2013 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/24612 Protein secondary structure prediction using amino acid regularities Barnard, E. fsenekal@csir.co.za Senekal, Frederick Petrus Amino acid sequence Neural network Classification Secondary structure Protein secondary structure prediction Bioinformatics Pattern recognition Protein folding problem Amino acid (AA) Protein UCTD Dissertation (MEng)--University of Pretoria, 2009. The protein folding problem is examined. Specifically, the problem of predicting protein secondary structure from the amino acid sequence is investigated. A literature study is presented into the protein folding process and the different techniques that currently exist to predict protein secondary structures. These techniques include the use of expert rules, statistics, information theory and various computational intelligence techniques, such as neural networks, nearest neighbour methods, Hidden Markov Models and Support Vector Machines. A pattern recognition technique based on statistical analysis is developed to predict protein secondary structure from the amino acid sequence. The technique can be applied to any problem where an input pattern is associated with an output pattern and each element in both the input and output patterns can take its value from a set with finite cardinality. The technique is applied to discover the role that small sequences of amino acids play in the formation of protein secondary structures. By applying the technique, a performance score of Q8 = 59:2% is achieved, with a corresponding Q3 score of 69.7%. This compares well with state of the art techniques, such as OSS-HMM and PSIPRED, which achieve Q3 scores of 67.9% and 66.8% respectively, when predictions on single sequences are made. Electrical, Electronic and Computer Engineering unrestricted 2013-09-06T18:03:53Z 2009-04-08 2013-09-06T18:03:53Z 2008-09-02 2009-04-08 2009-01-23 Dissertation 2008 E1196/gm http://hdl.handle.net/2263/24612 http://upetd.up.ac.za/thesis/available/etd-01232009-120040/ ©University of Pretoria 2008 E1196/ application/pdf University of Pretoria |
| spellingShingle | Amino acid sequence Neural network Classification Secondary structure Protein secondary structure prediction Bioinformatics Pattern recognition Protein folding problem Amino acid (AA) Protein UCTD Protein secondary structure prediction using amino acid regularities |
| title | Protein secondary structure prediction using amino acid regularities |
| title_full | Protein secondary structure prediction using amino acid regularities |
| title_fullStr | Protein secondary structure prediction using amino acid regularities |
| title_full_unstemmed | Protein secondary structure prediction using amino acid regularities |
| title_short | Protein secondary structure prediction using amino acid regularities |
| title_sort | protein secondary structure prediction using amino acid regularities |
| topic | Amino acid sequence Neural network Classification Secondary structure Protein secondary structure prediction Bioinformatics Pattern recognition Protein folding problem Amino acid (AA) Protein UCTD |
| url | http://hdl.handle.net/2263/24612 http://upetd.up.ac.za/thesis/available/etd-01232009-120040/ |