| Summary: | 碩士 === 國立清華大學 === 電機工程學系 === 93 === The completion of Human Genome Project has triggered a wave of investigating various
biological problems directly through the string of nucleotides and also its derived amino
acid sequence. Therefore, the urgent need of predicting protein three-dimensional structure
simply from the amino acid sequence propels us to develop a model-based method to predict
the composition of the fundamental structural elements–that is, secondary structures–of any
protein chain. To accomplish this goal, we first represent all the eligible secondary structure
sequences as specific paths in a secondary structure trellis. Then we employ the method
of dependency graphs and their expanded Bayesian networks to quantify the relationship
between primary and secondary structures. Following the similar procedure as in the coding
theory, we finally assign a secondary structure element to each amino acid through the use of
two decoding algorithms: the Viterbi algorithm and the sum-product algorithm. The simulation
results reveal that our proposed method achieves an accuracy that is indistinguishable
from other existing sequence-only methods, and that a better outcome is reached when the
target sequences are confined to a specific protein fold.
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