Prediction of DNA Binding Transcription Factor segments under Specified structure
碩士 === 國立臺灣大學 === 資訊工程學研究所 === 96 === This thesis discusses the design of a predictor aimed at identifying the secondary structures in a transcription factor that are involved in interaction with the DNA. In particular, the design of the predictor has been optimized for identifying the alpha-helix s...
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ndltd-TW-096NTU053921572015-11-25T04:04:25Z http://ndltd.ncl.edu.tw/handle/46288973583523923659 Prediction of DNA Binding Transcription Factor segments under Specified structure 預測轉錄因子上與去氧核醣酸結之區段 Jen-Jay Hsu 徐振傑 碩士 國立臺灣大學 資訊工程學研究所 96 This thesis discusses the design of a predictor aimed at identifying the secondary structures in a transcription factor that are involved in interaction with the DNA. In particular, the design of the predictor has been optimized for identifying the alpha-helix structures involved in interaction with the DNA due to their prevalence. In the design of the predictor, the support vector machine (SVM) was employed and the study reported in this thesis focused on the features exploited for making prediction. In the experiments conducted in this study, two datasets have been used. The first dataset was derived from the TF-DNA complexes deposited in the Protein Data Bank (PDB) and the second dataset was derived from the TF sequences deposited in SWISS-PROT. With respect to identifying the alpha-helix structures involved in interaction with the DNA, the predictor proposed in this thesis delivered sensitivity of 75%, precision of 80%, and specificity of 92% with the first dataset and sensitivity 65%, precision 85%, and specificity 98% with the second dataset. Yen-Jen Oyang 歐陽彥正 2008 學位論文 ; thesis 34 zh-TW |
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碩士 === 國立臺灣大學 === 資訊工程學研究所 === 96 === This thesis discusses the design of a predictor aimed at identifying the secondary structures in a transcription factor that are involved in interaction with the DNA. In particular, the design of the predictor has been optimized for identifying the alpha-helix structures involved in interaction with the DNA due to their prevalence. In the design of the predictor, the support vector machine (SVM) was employed and the study reported in this thesis focused on the features exploited for making prediction. In the experiments conducted in this study, two datasets have been used. The first dataset was derived from the TF-DNA complexes deposited in the Protein Data Bank (PDB) and the second dataset was derived from the TF sequences deposited in SWISS-PROT. With respect to identifying the alpha-helix structures involved in interaction with the DNA, the predictor proposed in this thesis delivered sensitivity of 75%, precision of 80%, and specificity of 92% with the first dataset and sensitivity 65%, precision 85%, and specificity 98% with the second dataset.
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Yen-Jen Oyang |
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Yen-Jen Oyang Jen-Jay Hsu 徐振傑 |
author |
Jen-Jay Hsu 徐振傑 |
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Jen-Jay Hsu 徐振傑 Prediction of DNA Binding Transcription Factor segments under Specified structure |
author_sort |
Jen-Jay Hsu |
title |
Prediction of DNA Binding Transcription Factor segments under Specified structure |
title_short |
Prediction of DNA Binding Transcription Factor segments under Specified structure |
title_full |
Prediction of DNA Binding Transcription Factor segments under Specified structure |
title_fullStr |
Prediction of DNA Binding Transcription Factor segments under Specified structure |
title_full_unstemmed |
Prediction of DNA Binding Transcription Factor segments under Specified structure |
title_sort |
prediction of dna binding transcription factor segments under specified structure |
publishDate |
2008 |
url |
http://ndltd.ncl.edu.tw/handle/46288973583523923659 |
work_keys_str_mv |
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