Prediction of DNA Binding Transcription Factor segments under Specified structure
Date Issued
2008
Date
2008
Author(s)
Hsu, Jen-Jay
Abstract
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.
Subjects
SVM
secondary structure
DNA
prediction
binding segments
Type
thesis
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