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  • Authors: Zaslavsky, Elena (2006)

  • A major objective in molecular biology is to understand how a genome encodes the information that speci es when and where a gene will be transcribed into its protein product. Mediating proteins, known as transcription factors, facilitate this process by interacting with the cell 's sDNA and the transcription machinery. It is of central importance to identify all sequence-speci c DNA binding sites of transcription factors. In this thesis, we consider two relevant computational problems. The first problem is to develop a representation for a group of known binding sites of a particular transcription factor, in order to facilitate recognition of other binding sites of the same protein. We evaluate the e ectiveness of several approaches commonly used for this problem, and show that the...

  • Thesis


  • Authors: Vinar, Tomas (2006)

  • In this thesis, we present enhancements of hidden Markov models for the problem of finding genes in DNA sequences. Genes are the parts of DNA that serve as a template for synthesis of proteins. Thus. gene finding is a crucial step in the analysis of DNA sequencing data. Hidden Markov models are a key tool used in gene finding. Yhis thesis presents three methods for extending the capabilities of hidden Markov models to better capture the statistical properties of DNA sequences. In all three, we encounter limiting factors that lead to trade-offs between the model accuracy and those limiting factors. First. we build better models for recognizing biological signals in DNA sequences. Our new models capture non-adjacent dependencies within these signals. In this case. the main limiting ...