|
Prediction and Analysis of Nucleosome Positions in DNA
Višňovský, Marek ; Bendl, Jaroslav (oponent) ; Martínek, Tomáš (vedoucí práce)
Genomic DNA in eukaryotes wraps around nucleosomes, which thereby affects higher order DNA structure and access to genomic features like transcription factor binding sites (TFBSs) and gene regions. It is therefore important to have a good understanding of where nucleosomes bind to DNA, and how stable this binding is, in order to understand gene regulation. We developed, implemented and tested a novel approach for genome-wide predictions of nucleosome positions in yeast based on Hidden Markov models extended by duration modeling, using data from Brogaard et al. (Brogaard K, Wang J-P, Widom, J. Nature 486(7404), 496-501 (2012). doi:10.1038/nature11142) for training and testing. Achieved sensitivity closing to 50% does not improve performance compared to other existing methods. In addition, several experiments were conducted on the available dataset to identify features of sequences occupied by nucleosomes and theirs global organization that are important for the prediction performance.
|
|
Prediction and Analysis of Nucleosome Positions in DNA
Višňovský, Marek ; Bendl, Jaroslav (oponent) ; Martínek, Tomáš (vedoucí práce)
Genomic DNA in eukaryotes wraps around nucleosomes, which thereby affects higher order DNA structure and access to genomic features like transcription factor binding sites (TFBSs) and gene regions. It is therefore important to have a good understanding of where nucleosomes bind to DNA, and how stable this binding is, in order to understand gene regulation. We developed, implemented and tested a novel approach for genome-wide predictions of nucleosome positions in yeast based on Hidden Markov models extended by duration modeling, using data from Brogaard et al. (Brogaard K, Wang J-P, Widom, J. Nature 486(7404), 496-501 (2012). doi:10.1038/nature11142) for training and testing. Achieved sensitivity closing to 50% does not improve performance compared to other existing methods. In addition, several experiments were conducted on the available dataset to identify features of sequences occupied by nucleosomes and theirs global organization that are important for the prediction performance.
|